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2012
Ebden, Mark; Huynh, Trung Dong; Moreau, Luc; Ramchurn, Sarvapali; Stephen, Roberts
Network analysis on provenance graphs from a crowdsourcing application Proceedings Article
In: Groth, Paul; Frew, James (Ed.): 4th International Provenance and Annotation Workshop, pp. 168–182, 2012.
Abstract | Links | BibTeX | Tags: collabmap, crowdsourcing, densification, evacuation, graph diameters, maps, network analysis, node degree, provenance, provenance graphs
@inproceedings{eps340068,
title = {Network analysis on provenance graphs from a crowdsourcing application},
author = {Mark Ebden and Trung Dong Huynh and Luc Moreau and Sarvapali Ramchurn and Roberts Stephen},
editor = {Paul Groth and James Frew},
url = {http://eprints.soton.ac.uk/340068/},
year = {2012},
date = {2012-01-01},
booktitle = {4th International Provenance and Annotation Workshop},
volume = {7525},
pages = {168–182},
series = {0302-9743},
abstract = {Crowdsourcing has become a popular means for quickly achieving various tasks in large quantities. CollabMap is an online mapping application in which we crowdsource the identification of evacuation routes in residential areas to be used for planning large-scale evacuations. So far, approximately 38,000 micro-tasks have been completed by over 100 contributors. In order to assist with data verification, we introduced provenance tracking into the application, and approximately 5,000 provenance graphs have been generated. They have provided us various insights into the typical characteristics of provenance graphs in the crowdsourcing context. In particular, we have estimated probability distribution functions over three selected characteristics of these provenance graphs: the node degree, the graph diameter, and the densification exponent. We describe methods to define these three characteristics across specific combinations of node types and edge types, and present our findings in this paper. Applications of our methods include rapid comparison of one provenance graph versus another, or of one style of provenance database versus another. Our results also indicate that provenance graphs represent a suitable area of exploitation for existing network analysis tools concerned with modelling, prediction, and the inference of missing nodes and edges.},
keywords = {collabmap, crowdsourcing, densification, evacuation, graph diameters, maps, network analysis, node degree, provenance, provenance graphs},
pubstate = {published},
tppubtype = {inproceedings}
}
Crowdsourcing has become a popular means for quickly achieving various tasks in large quantities. CollabMap is an online mapping application in which we crowdsource the identification of evacuation routes in residential areas to be used for planning large-scale evacuations. So far, approximately 38,000 micro-tasks have been completed by over 100 contributors. In order to assist with data verification, we introduced provenance tracking into the application, and approximately 5,000 provenance graphs have been generated. They have provided us various insights into the typical characteristics of provenance graphs in the crowdsourcing context. In particular, we have estimated probability distribution functions over three selected characteristics of these provenance graphs: the node degree, the graph diameter, and the densification exponent. We describe methods to define these three characteristics across specific combinations of node types and edge types, and present our findings in this paper. Applications of our methods include rapid comparison of one provenance graph versus another, or of one style of provenance database versus another. Our results also indicate that provenance graphs represent a suitable area of exploitation for existing network analysis tools concerned with modelling, prediction, and the inference of missing nodes and edges.
Matthews, Tim; Ramchurn, Sarvapali; Chalkiadakis, Georgios
Competing with humans at fantasy football: team formation in large partially-observable domains Proceedings Article
In: Proceedings of the Twenty-Sixth Conference on Artificial Intelligence, pp. 1394–1400, Association for the Advancement of Artificial Intelligence, 2012.
Abstract | Links | BibTeX | Tags: multi-agent systems, optimisation, sequential decision making, team formation
@inproceedings{eps340382,
title = {Competing with humans at fantasy football: team formation in large partially-observable domains},
author = {Tim Matthews and Sarvapali Ramchurn and Georgios Chalkiadakis},
url = {http://eprints.soton.ac.uk/340382/},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings of the Twenty-Sixth Conference on Artificial Intelligence},
pages = {1394–1400},
publisher = {Association for the Advancement of Artificial Intelligence},
abstract = {We present the first real-world benchmark for sequentially optimal team formation, working within the framework of a class of online football prediction games known as Fantasy Football. We model the problem as a Bayesian reinforcement learning one, where the action space is exponential in the number of players and where the decision maker?s beliefs are over multiple characteristics of each footballer. We then exploit domain knowledge to construct computationally tractable solution techniques in order to build a competitive automated Fantasy Football manager. Thus, we are able to establish the baseline performance in this domain, even without complete information on footballers? performances (accessible to human managers), showing that our agent is able to rank at around the top percentile when pitched against 2.5M human players},
keywords = {multi-agent systems, optimisation, sequential decision making, team formation},
pubstate = {published},
tppubtype = {inproceedings}
}
We present the first real-world benchmark for sequentially optimal team formation, working within the framework of a class of online football prediction games known as Fantasy Football. We model the problem as a Bayesian reinforcement learning one, where the action space is exponential in the number of players and where the decision maker?s beliefs are over multiple characteristics of each footballer. We then exploit domain knowledge to construct computationally tractable solution techniques in order to build a competitive automated Fantasy Football manager. Thus, we are able to establish the baseline performance in this domain, even without complete information on footballers? performances (accessible to human managers), showing that our agent is able to rank at around the top percentile when pitched against 2.5M human players
Miller, Sam; Ramchurn, Sarvapali D; Rogers, Alex
Optimal Decentralised Dispatch of Embedded Generation in the Smart Grid Journal Article
In: In Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2012.
Abstract | Links | BibTeX | Tags: Energy, human-agent interaction, smart grid
@article{eps273142,
title = {Optimal Decentralised Dispatch of Embedded Generation in the Smart Grid},
author = {Sam Miller and Sarvapali D Ramchurn and Alex Rogers},
url = {http://eprints.soton.ac.uk/273142/},
year = {2012},
date = {2012-01-01},
booktitle = {Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS)},
journal = {In Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS)},
abstract = {Distribution network operators face a number of challenges; capacity constrained networks, and balancing electricity demand with generation from intermittent renewable resources. Thus, there is an increasing need for scalable approaches to facilitate optimal dispatch in the distribution network. To this end, we cast the optimal dispatch problem as a decentralised agent-based coordination problem and formalise it as a DCOP. We show how this can be decomposed as a factor graph and solved in a decentralised manner using algorithms based on the generalised distributive law; in particular, the max-sum algorithm. We go on to show that max-sum applied na?vely in this setting performs a large number of redundant computations. To address this issue, we present a novel decentralised message passing algorithm using dynamic programming that outperforms max-sum by pruning the search space. We empirically evaluate our algorithm using real distribution network data, showing that it outperforms (in terms of computational time and total size of messages sent) both a centralised approach, which uses IBM?s ILOG CPLEX 12.2, and max-sum, for large networks.},
keywords = {Energy, human-agent interaction, smart grid},
pubstate = {published},
tppubtype = {article}
}
Distribution network operators face a number of challenges; capacity constrained networks, and balancing electricity demand with generation from intermittent renewable resources. Thus, there is an increasing need for scalable approaches to facilitate optimal dispatch in the distribution network. To this end, we cast the optimal dispatch problem as a decentralised agent-based coordination problem and formalise it as a DCOP. We show how this can be decomposed as a factor graph and solved in a decentralised manner using algorithms based on the generalised distributive law; in particular, the max-sum algorithm. We go on to show that max-sum applied na?vely in this setting performs a large number of redundant computations. To address this issue, we present a novel decentralised message passing algorithm using dynamic programming that outperforms max-sum by pruning the search space. We empirically evaluate our algorithm using real distribution network data, showing that it outperforms (in terms of computational time and total size of messages sent) both a centralised approach, which uses IBM?s ILOG CPLEX 12.2, and max-sum, for large networks.
Ramchurn, Sarvapali; Vytelingum, Perukrishnen; Rogers, Alex; Jennings, Nicholas R.
Putting the Smarts into the Smart Grid: A Grand Challenge for Artificial Intelligence Journal Article
In: Communications of the ACM, vol. 55, no. 4, pp. 86–97, 2012.
Abstract | Links | BibTeX | Tags: electricity, Energy, smart grid, smart home
@article{eps272606,
title = {Putting the Smarts into the Smart Grid: A Grand Challenge for Artificial Intelligence},
author = {Sarvapali Ramchurn and Perukrishnen Vytelingum and Alex Rogers and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/272606/},
year = {2012},
date = {2012-01-01},
journal = {Communications of the ACM},
volume = {55},
number = {4},
pages = {86–97},
publisher = {ACM},
abstract = {The phenomenal growth in material wealth experienced in developed countries throughout the twentieth century has largely been driven by the availability of cheap energy derived from fossil fuels (originally coal, then oil, and most recently natural gas). However, the continued availability of this cheap energy cannot be taken for granted given the growing concern that increasing demand for these fuels (and particularly, demand for oil) will outstrip our ability to produce them (so called `peak oil'). Many mature oil and gas fields around the world have already peaked and their annual production is now steadily declining. Predictions of when world oil production will peak vary between 0-20 years into the future, but even the most conservative estimates provide little scope for complacency given the significant price increases that peak oil is likely to precipitate. Furthermore, many of the oil and gas reserves that do remain are in environmentally or politically sensitive regions of the world where threats to supply create increased price volatility (as evidenced by the 2010 Deepwater Horizon disaster and 2011 civil unrest in the Middle East). Finally, the growing consensus on the long term impact of carbon emissions from burning fossil fuels suggests that even if peak oil is avoided, and energy security assured, a future based on fossil fuel use will expose regions of the world to damaging climate change that will make the lives of many of the world's poorest people even harder.},
keywords = {electricity, Energy, smart grid, smart home},
pubstate = {published},
tppubtype = {article}
}
The phenomenal growth in material wealth experienced in developed countries throughout the twentieth century has largely been driven by the availability of cheap energy derived from fossil fuels (originally coal, then oil, and most recently natural gas). However, the continued availability of this cheap energy cannot be taken for granted given the growing concern that increasing demand for these fuels (and particularly, demand for oil) will outstrip our ability to produce them (so called `peak oil'). Many mature oil and gas fields around the world have already peaked and their annual production is now steadily declining. Predictions of when world oil production will peak vary between 0-20 years into the future, but even the most conservative estimates provide little scope for complacency given the significant price increases that peak oil is likely to precipitate. Furthermore, many of the oil and gas reserves that do remain are in environmentally or politically sensitive regions of the world where threats to supply create increased price volatility (as evidenced by the 2010 Deepwater Horizon disaster and 2011 civil unrest in the Middle East). Finally, the growing consensus on the long term impact of carbon emissions from burning fossil fuels suggests that even if peak oil is avoided, and energy security assured, a future based on fossil fuel use will expose regions of the world to damaging climate change that will make the lives of many of the world's poorest people even harder.
Ramchurn, Sarvapali D.; Gerding, Enrico; Jennings, N. R.; Hu, Jun
Practical distributed coalition formation via heuristic negotiation in social networks Proceedings Article
In: Fifth International Workshop on Optimisation in Multi-Agent Systems (OPTMAS), 2012.
Abstract | Links | BibTeX | Tags: mas, multi-agent systems
@inproceedings{eps344492,
title = {Practical distributed coalition formation via heuristic negotiation in social networks},
author = {Sarvapali D. Ramchurn and Enrico Gerding and N. R. Jennings and Jun Hu},
url = {http://eprints.soton.ac.uk/344492/},
year = {2012},
date = {2012-01-01},
booktitle = {Fifth International Workshop on Optimisation in Multi-Agent Systems (OPTMAS)},
abstract = {We present a novel framework for decentralised coalition formation in social networks, where agents can form coalitions through bilateral negotiations with their neighbours. Specifically, we present a practical negotiation protocol and decision functions that enable agents to form coalitions with agents beyond their peers. Building on this, we establish baseline negotiation strategies which we empirically show to be efficient (agreements are reached in few negotiation rounds) and effective (agreements have high utility compared to a centralised approach) on a variety of network topologies. Moreover, we show that the average degree of social networks can significantly affect the performance of these strategies.},
keywords = {mas, multi-agent systems},
pubstate = {published},
tppubtype = {inproceedings}
}
We present a novel framework for decentralised coalition formation in social networks, where agents can form coalitions through bilateral negotiations with their neighbours. Specifically, we present a practical negotiation protocol and decision functions that enable agents to form coalitions with agents beyond their peers. Building on this, we establish baseline negotiation strategies which we empirically show to be efficient (agreements are reached in few negotiation rounds) and effective (agreements have high utility compared to a centralised approach) on a variety of network topologies. Moreover, we show that the average degree of social networks can significantly affect the performance of these strategies.
Richardson, Darren P.; Costanza, Enrico; Ramchurn, Sarvapali D.
Evaluating semi-automatic annotation of domestic energy consumption as a memory aid Proceedings Article
In: UbiComp '12 Proceedings of the 2012 ACM Conference on Ubiquitous Computing, pp. 613–614, 2012.
Abstract | Links | BibTeX | Tags: Energy, hai, home energy management, human-agent interaction
@inproceedings{eps349083,
title = {Evaluating semi-automatic annotation of domestic energy consumption as a memory aid},
author = {Darren P. Richardson and Enrico Costanza and Sarvapali D. Ramchurn},
url = {http://eprints.soton.ac.uk/349083/},
year = {2012},
date = {2012-01-01},
booktitle = {UbiComp '12 Proceedings of the 2012 ACM Conference on Ubiquitous Computing},
pages = {613–614},
abstract = {Frequent feedback about energy consumption can help conservation, one of the current global challenges. Such feedback is most helpful if users can relate it to their own day-to-day activities. In earlier work we showed that manual annotation of domestic energy consumption logs aids users to make such connection and discover patterns they were not aware of. In this poster we report how we augmented manual annotation with machine learning classification techniques. We propose the design of a lab study to evaluate the system, extending methods used to evaluate context aware memory aids, and we present the results of a pilot with 5 participants.},
keywords = {Energy, hai, home energy management, human-agent interaction},
pubstate = {published},
tppubtype = {inproceedings}
}
Frequent feedback about energy consumption can help conservation, one of the current global challenges. Such feedback is most helpful if users can relate it to their own day-to-day activities. In earlier work we showed that manual annotation of domestic energy consumption logs aids users to make such connection and discover patterns they were not aware of. In this poster we report how we augmented manual annotation with machine learning classification techniques. We propose the design of a lab study to evaluate the system, extending methods used to evaluate context aware memory aids, and we present the results of a pilot with 5 participants.
Rogers, Alex; Ramchurn, Sarvapali; Jennings, Nicholas R.
Delivering the smart grid: Challenges for autonomous agents and multi-agent systems research Proceedings Article
In: Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12), pp. 2166–2172, 2012.
Abstract | Links | BibTeX | Tags: electricity, Energy, home energy management
@inproceedings{eps337560,
title = {Delivering the smart grid: Challenges for autonomous agents and multi-agent systems research},
author = {Alex Rogers and Sarvapali Ramchurn and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/337560/},
year = {2012},
date = {2012-01-01},
booktitle = {Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12)},
pages = {2166–2172},
abstract = {Restructuring electricity grids to meet the increased demand caused by the electrification of transport and heating, while making greater use of intermittent renewable energy sources, represents one of the greatest engineering challenges of our day. This modern electric- ity grid, in which both electricity and information flow in two directions between large numbers of widely dis- tributed suppliers and generators – commonly termed the ?smart grid? – represents a radical reengineering of infrastructure which has changed little over the last hundred years. However, the autonomous behaviour expected of the smart grid, its distributed nature, and the existence of multiple stakeholders each with their own incentives and interests, challenges existing engineering approaches. In this challenge paper, we describe why we believe that artificial intelligence, and particularly, the fields of autonomous agents and multi-agent systems are essential for delivering the smart grid as it is envisioned. We present some recent work in this area and describe many of the challenges that still remain.},
keywords = {electricity, Energy, home energy management},
pubstate = {published},
tppubtype = {inproceedings}
}
Restructuring electricity grids to meet the increased demand caused by the electrification of transport and heating, while making greater use of intermittent renewable energy sources, represents one of the greatest engineering challenges of our day. This modern electric- ity grid, in which both electricity and information flow in two directions between large numbers of widely dis- tributed suppliers and generators – commonly termed the ?smart grid? – represents a radical reengineering of infrastructure which has changed little over the last hundred years. However, the autonomous behaviour expected of the smart grid, its distributed nature, and the existence of multiple stakeholders each with their own incentives and interests, challenges existing engineering approaches. In this challenge paper, we describe why we believe that artificial intelligence, and particularly, the fields of autonomous agents and multi-agent systems are essential for delivering the smart grid as it is envisioned. We present some recent work in this area and describe many of the challenges that still remain.
Truong, Ngoc Cuong; Tran-Thanh, Long; Costanza, Enrico; Ramchurn, Sarvapali D.
Predicting energy consumption activities for home energy management Proceedings Article
In: Agent Technologies for Energy Systems (ATES 2012), 2012.
Links | BibTeX | Tags: Energy, human-agent interaction, smart grid, smart home
@inproceedings{eps339215,
title = {Predicting energy consumption activities for home energy management},
author = {Ngoc Cuong Truong and Long Tran-Thanh and Enrico Costanza and Sarvapali D. Ramchurn},
url = {http://eprints.soton.ac.uk/339215/},
year = {2012},
date = {2012-01-01},
booktitle = {Agent Technologies for Energy Systems (ATES 2012)},
keywords = {Energy, human-agent interaction, smart grid, smart home},
pubstate = {published},
tppubtype = {inproceedings}
}
Voice, Thomas; Ramchurn, Sarvapali; Jennings, Nick
On coalition formation with sparse synergies Proceedings Article
In: Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), pp. 223–230, 2012.
@inproceedings{eps273083,
title = {On coalition formation with sparse synergies},
author = {Thomas Voice and Sarvapali Ramchurn and Nick Jennings},
url = {http://eprints.soton.ac.uk/273083/},
year = {2012},
date = {2012-01-01},
booktitle = {Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS)},
pages = {223–230},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Simpson, Edwin; Reece, Steven; Penta, Antonio; Ramchurn, Sarvapali D
Using a Bayesian Model to Combine LDA Features with Crowdsourced Responses Proceedings Article
In: Proceedings of The Twenty-First Text REtrieval Conference, TREC 2012, Gaithersburg, Maryland, USA, November 6-9, 2012, 2012.
@inproceedings{DBLP:conf/trec/SimpsonRPR12,
title = {Using a Bayesian Model to Combine LDA Features with Crowdsourced
Responses},
author = {Edwin Simpson and Steven Reece and Antonio Penta and Sarvapali D Ramchurn},
url = {http://trec.nist.gov/pubs/trec21/papers/HAC.crowd.final.pdf},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings of The Twenty-First Text REtrieval Conference, TREC
2012, Gaithersburg, Maryland, USA, November 6-9, 2012},
crossref = {DBLP:conf/trec/2012},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
2011
Alam, Muddasser; Rogers, Alex; Ramchurn, Sarvapali
A negotiation protocol for multiple interdependent issues negotiation over energy exchange Proceedings Article
In: IJCAI Workshop on AI for an Intelligent Planet, 2011, (Event Dates: July-16).
Abstract | Links | BibTeX | Tags: Multiagent Systems Negotiation Protocol Rules of encounter Multiissue Negotiation Interdependent multi issue negotiation
@inproceedings{eps272479,
title = {A negotiation protocol for multiple interdependent issues negotiation over energy exchange},
author = {Muddasser Alam and Alex Rogers and Sarvapali Ramchurn},
url = {http://eprints.soton.ac.uk/272479/},
year = {2011},
date = {2011-01-01},
booktitle = {IJCAI Workshop on AI for an Intelligent Planet},
abstract = {We present a novel negotiation protocol to facilitate energy exchange between off-grid homes that are equipped with renewable energy generation and electricity storage. Our solution imposes additional constraints on negotiation such that it reduces a complex interdependent multi-issue problem to one that is tractable. We prove that using our protocol, agents can reach a Pareto-optimal, dominant strategy equilibrium in a decentralized and timely fashion. We empirically evaluate our approach in a realistic setting. In this case, we show that energy exchange can be useful in reducing the capacity of the energy storage devices in homes by close to 40%},
note = {Event Dates: July-16},
keywords = {Multiagent Systems Negotiation Protocol Rules of encounter Multiissue Negotiation Interdependent multi issue negotiation},
pubstate = {published},
tppubtype = {inproceedings}
}
We present a novel negotiation protocol to facilitate energy exchange between off-grid homes that are equipped with renewable energy generation and electricity storage. Our solution imposes additional constraints on negotiation such that it reduces a complex interdependent multi-issue problem to one that is tractable. We prove that using our protocol, agents can reach a Pareto-optimal, dominant strategy equilibrium in a decentralized and timely fashion. We empirically evaluate our approach in a realistic setting. In this case, we show that energy exchange can be useful in reducing the capacity of the energy storage devices in homes by close to 40%
Macarthur, Kathryn; Stranders, Ruben; Ramchurn, Sarvapali; Jennings, Nick
A Distributed Anytime Algorithm for Dynamic Task Allocation in Multi-Agent Systems Proceedings Article
In: Twenty-Fifth Conference on Artificial Intelligence (AAAI), pp. 701–706, AAAI Press, 2011, (Event Dates: August 7-11, 2011).
Abstract | Links | BibTeX | Tags: mas, Multi-agent scheduling, multi-agent systems
@inproceedings{eps272233,
title = {A Distributed Anytime Algorithm for Dynamic Task Allocation in Multi-Agent Systems},
author = {Kathryn Macarthur and Ruben Stranders and Sarvapali Ramchurn and Nick Jennings},
url = {http://eprints.soton.ac.uk/272233/},
year = {2011},
date = {2011-01-01},
booktitle = {Twenty-Fifth Conference on Artificial Intelligence (AAAI)},
pages = {701–706},
publisher = {AAAI Press},
abstract = {We introduce a novel distributed algorithm for multi-agent task allocation problems where the sets of tasks and agents constantly change over time. We build on an existing anytime algorithm (fast-max-sum), and give it significant new capa- bilities: namely, an online pruning procedure that simplifies the problem, and a branch-and-bound technique that reduces the search space. This allows us to scale to problems with hundreds of tasks and agents. We empirically evaluate our algorithm against established benchmarks and find that, even in such large environments, a solution is found up to 31% faster, and with up to 23% more utility, than state-of-the-art approximation algorithms. In addition, our algorithm sends up to 30% fewer messages than current approaches when the set of agents or tasks changes.},
note = {Event Dates: August 7-11, 2011},
keywords = {mas, Multi-agent scheduling, multi-agent systems},
pubstate = {published},
tppubtype = {inproceedings}
}
We introduce a novel distributed algorithm for multi-agent task allocation problems where the sets of tasks and agents constantly change over time. We build on an existing anytime algorithm (fast-max-sum), and give it significant new capa- bilities: namely, an online pruning procedure that simplifies the problem, and a branch-and-bound technique that reduces the search space. This allows us to scale to problems with hundreds of tasks and agents. We empirically evaluate our algorithm against established benchmarks and find that, even in such large environments, a solution is found up to 31% faster, and with up to 23% more utility, than state-of-the-art approximation algorithms. In addition, our algorithm sends up to 30% fewer messages than current approaches when the set of agents or tasks changes.
Macarthur, Kathryn; Vinyals, Meritxell; Farinelli, Alessandro; Ramchurn, Sarvapali; Jennings, Nick
Decentralised Parallel Machine Scheduling for Multi-Agent Task Allocation Proceedings Article
In: Fourth International Workshop on Optimisation in Multi-Agent Systems, 2011, (Event Dates: May 3, 2011).
Abstract | Links | BibTeX | Tags: mas, Multi-agent scheduling, multi-agent systems
@inproceedings{eps272234,
title = {Decentralised Parallel Machine Scheduling for Multi-Agent Task Allocation},
author = {Kathryn Macarthur and Meritxell Vinyals and Alessandro Farinelli and Sarvapali Ramchurn and Nick Jennings},
url = {http://eprints.soton.ac.uk/272234/},
year = {2011},
date = {2011-01-01},
booktitle = {Fourth International Workshop on Optimisation in Multi-Agent Systems},
abstract = {Multi-agent task allocation problems pervade a wide range of real-world applications, such as search and rescue in disaster manage- ment, or grid computing. In these applications, where agents are given tasks to perform in parallel, it is often the case that the performance of all agents is judged based on the time taken by the slowest agent to complete its tasks. Hence, efficient distribution of tasks across het- erogeneous agents is important to ensure a short completion time. An equivalent problem to this can be found in operations research, and is known as scheduling jobs on unrelated parallel machines (also known as Rensuremath|ensuremath|Cmax). In this paper, we draw parallels between unrelated parallel machine scheduling and multi-agent task allocation problems, and, in so doing, we present the decentralised task distribution algorithm (DTDA), the first decentralised solution to Rensuremath|ensuremath|Cmax. Empirical evaluation of the DTDA is shown to generate solutions within 86?97% of the optimal on sparse graphs, in the best case, whilst providing a very good estimate (within 1%) of the global solution at each agent.},
note = {Event Dates: May 3, 2011},
keywords = {mas, Multi-agent scheduling, multi-agent systems},
pubstate = {published},
tppubtype = {inproceedings}
}
Multi-agent task allocation problems pervade a wide range of real-world applications, such as search and rescue in disaster manage- ment, or grid computing. In these applications, where agents are given tasks to perform in parallel, it is often the case that the performance of all agents is judged based on the time taken by the slowest agent to complete its tasks. Hence, efficient distribution of tasks across het- erogeneous agents is important to ensure a short completion time. An equivalent problem to this can be found in operations research, and is known as scheduling jobs on unrelated parallel machines (also known as Rensuremath|ensuremath|Cmax). In this paper, we draw parallels between unrelated parallel machine scheduling and multi-agent task allocation problems, and, in so doing, we present the decentralised task distribution algorithm (DTDA), the first decentralised solution to Rensuremath|ensuremath|Cmax. Empirical evaluation of the DTDA is shown to generate solutions within 86?97% of the optimal on sparse graphs, in the best case, whilst providing a very good estimate (within 1%) of the global solution at each agent.
Osborne, Michael A.; Rogers, Alex; Roberts, Stephen J.; Ramchurn, Sarvapali D.; Jennings, Nicholas R.
Gaussian Processes for Time Series Prediction Book Section
In: Bayesian Time Series Models, pp. 341–360, Cambridge University Press, 2011, (Chapter: 16).
Links | BibTeX | Tags: machine learning, mas
@incollection{eps272746,
title = {Gaussian Processes for Time Series Prediction},
author = {Michael A. Osborne and Alex Rogers and Stephen J. Roberts and Sarvapali D. Ramchurn and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/272746/},
year = {2011},
date = {2011-01-01},
booktitle = {Bayesian Time Series Models},
pages = {341–360},
publisher = {Cambridge University Press},
note = {Chapter: 16},
keywords = {machine learning, mas},
pubstate = {published},
tppubtype = {incollection}
}
Ramchurn, Sarvapali; Vytelingum, Perukrishnen; Rogers, Alex; Jennings, Nick
Agent-based homeostatic control for green energy in the smart grid Journal Article
In: ACM Transactions on Intelligent Systems and Technology, vol. 2, no. 4, pp. 35:1–35:28, 2011.
Abstract | Links | BibTeX | Tags: Energy, mas, multi-agent systems
@article{eps272015,
title = {Agent-based homeostatic control for green energy in the smart grid},
author = {Sarvapali Ramchurn and Perukrishnen Vytelingum and Alex Rogers and Nick Jennings},
url = {http://eprints.soton.ac.uk/272015/},
year = {2011},
date = {2011-01-01},
journal = {ACM Transactions on Intelligent Systems and Technology},
volume = {2},
number = {4},
pages = {35:1–35:28},
abstract = {With dwindling non-renewable energy reserves and the adverse effects of climate change, the development of the smart electricity grid is seen as key to solving global energy security issues and to reducing carbon emissions. In this respect, there is a growing need to integrate renewable (or green) energy sources in the grid. However, the intermittency of these energy sources requires that demand must also be made more responsive to changes in supply, and a number of smart grid technologies are being developed, such as high-capacity batteries and smart meters for the home, to enable consumers to be more responsive to conditions on the grid in real-time. Traditional solutions based on these technologies, however, tend to ignore the fact that individual consumers will behave in such a way that best satisfies their own preferences to use or store energy (as opposed to that of the supplier or the grid operator). Hence, in practice, it is unclear how these solutions will cope with large numbers of consumers using their devices in this way. Against this background, in this paper, we develop novel control mechanisms based on the use of autonomous agents to better incorporate consumer preferences in managing demand. These agents, residing on consumers' smart meters, can both communicate with the grid and optimise their owner's energy consumption to satisfy their preferences. More specifically, we provide a novel control mechanism that models and controls a system comprising of a green energy supplier operating within the grid and a number of individual homes (each possibly owning a storage device). This control mechanism is based on the concept of homeostasis whereby control signals are sent to individual components of a system, based on their continuous feedback, in order to change their state so that the system may reach a stable equilibrium. Thus, we define a new carbon-based pricing mechanism for this green energy supplier that takes advantage of carbon-intensity signals available on the internet in order to provide real-time pricing. The pricing scheme is designed in such a way that it can be readily implemented using existing communication technologies and is easily understandable by consumers. Building upon this, we develop new control signals that the supplier can use to incentivise agents to shift demand (using their storage device) to times when green energy is available. Moreover, we show how these signals can be adapted according to changes in supply and to various degrees of penetration of storage in the system. We empirically evaluate our system and show that, when all homes are equipped with storage devices, the supplier can significantly reduce its reliance on other carbon-emitting power sources to cater for its own shortfalls. By so doing, the supplier reduces the carbon emission of the system by up to 25% while the consumer reduces its costs by up to 14.5%. Finally, we demonstrate that our homeostatic control mechanism is not sensitive to small prediction errors and the supplier is incentivised to accurately predict its green production to minimise costs.},
keywords = {Energy, mas, multi-agent systems},
pubstate = {published},
tppubtype = {article}
}
With dwindling non-renewable energy reserves and the adverse effects of climate change, the development of the smart electricity grid is seen as key to solving global energy security issues and to reducing carbon emissions. In this respect, there is a growing need to integrate renewable (or green) energy sources in the grid. However, the intermittency of these energy sources requires that demand must also be made more responsive to changes in supply, and a number of smart grid technologies are being developed, such as high-capacity batteries and smart meters for the home, to enable consumers to be more responsive to conditions on the grid in real-time. Traditional solutions based on these technologies, however, tend to ignore the fact that individual consumers will behave in such a way that best satisfies their own preferences to use or store energy (as opposed to that of the supplier or the grid operator). Hence, in practice, it is unclear how these solutions will cope with large numbers of consumers using their devices in this way. Against this background, in this paper, we develop novel control mechanisms based on the use of autonomous agents to better incorporate consumer preferences in managing demand. These agents, residing on consumers' smart meters, can both communicate with the grid and optimise their owner's energy consumption to satisfy their preferences. More specifically, we provide a novel control mechanism that models and controls a system comprising of a green energy supplier operating within the grid and a number of individual homes (each possibly owning a storage device). This control mechanism is based on the concept of homeostasis whereby control signals are sent to individual components of a system, based on their continuous feedback, in order to change their state so that the system may reach a stable equilibrium. Thus, we define a new carbon-based pricing mechanism for this green energy supplier that takes advantage of carbon-intensity signals available on the internet in order to provide real-time pricing. The pricing scheme is designed in such a way that it can be readily implemented using existing communication technologies and is easily understandable by consumers. Building upon this, we develop new control signals that the supplier can use to incentivise agents to shift demand (using their storage device) to times when green energy is available. Moreover, we show how these signals can be adapted according to changes in supply and to various degrees of penetration of storage in the system. We empirically evaluate our system and show that, when all homes are equipped with storage devices, the supplier can significantly reduce its reliance on other carbon-emitting power sources to cater for its own shortfalls. By so doing, the supplier reduces the carbon emission of the system by up to 25% while the consumer reduces its costs by up to 14.5%. Finally, we demonstrate that our homeostatic control mechanism is not sensitive to small prediction errors and the supplier is incentivised to accurately predict its green production to minimise costs.
Ramchurn, Sarvapali; Vytelingum, Perukrishnen; Rogers, Alex; Jennings, Nick
Agent-based control for decentralised demand side management in the smart grid Proceedings Article
In: The Tenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), pp. 5–12, 2011.
Abstract | Links | BibTeX | Tags: agent-based control, agents, demand-side management electricity, Energy, multi-agent systems
@inproceedings{eps271985,
title = {Agent-based control for decentralised demand side management in the smart grid},
author = {Sarvapali Ramchurn and Perukrishnen Vytelingum and Alex Rogers and Nick Jennings},
url = {http://eprints.soton.ac.uk/271985/},
year = {2011},
date = {2011-01-01},
booktitle = {The Tenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011)},
pages = {5–12},
abstract = {Central to the vision of the smart grid is the deployment of smart meters that will allow autonomous software agents, representing the consumers, to optimise their use of devices and heating in the smart home while interacting with the grid. However, without some form of coordination, the population of agents may end up with overly-homogeneous optimised consumption patterns that may generate significant peaks in demand in the grid. These peaks, in turn, reduce the efficiency of the overall system, increase carbon emissions, and may even, in the worst case, cause blackouts. Hence, in this paper, we introduce a novel model of a Decentralised Demand Side Management (DDSM) mechanism that allows agents, by adapting the deferment of their loads based on grid prices, to coordinate in a decentralised manner. Specifically, using average UK consumption profiles for 26M homes, we demonstrate that, through an emergent coordination of the agents, the peak demand of domestic consumers in the grid can be reduced by up to 17% and carbon emissions by up to 6%. We also show that our DDSM mechanism is robust to the increasing electrification of heating in UK homes (i.e. it exhibits a similar efficiency).},
keywords = {agent-based control, agents, demand-side management electricity, Energy, multi-agent systems},
pubstate = {published},
tppubtype = {inproceedings}
}
Central to the vision of the smart grid is the deployment of smart meters that will allow autonomous software agents, representing the consumers, to optimise their use of devices and heating in the smart home while interacting with the grid. However, without some form of coordination, the population of agents may end up with overly-homogeneous optimised consumption patterns that may generate significant peaks in demand in the grid. These peaks, in turn, reduce the efficiency of the overall system, increase carbon emissions, and may even, in the worst case, cause blackouts. Hence, in this paper, we introduce a novel model of a Decentralised Demand Side Management (DDSM) mechanism that allows agents, by adapting the deferment of their loads based on grid prices, to coordinate in a decentralised manner. Specifically, using average UK consumption profiles for 26M homes, we demonstrate that, through an emergent coordination of the agents, the peak demand of domestic consumers in the grid can be reduced by up to 17% and carbon emissions by up to 6%. We also show that our DDSM mechanism is robust to the increasing electrification of heating in UK homes (i.e. it exhibits a similar efficiency).
Stranders, Ruben; Ramchurn, Sarvapali; Shi, Bing; Jennings, Nick
CollabMap: Augmenting Maps using the Wisdom of Crowds Proceedings Article
In: Third Human Computation Workshop, 2011.
Links | BibTeX | Tags: Disaster Management, human-agent interaction, mas, multi-agent systems
@inproceedings{eps272478,
title = {CollabMap: Augmenting Maps using the Wisdom of Crowds},
author = {Ruben Stranders and Sarvapali Ramchurn and Bing Shi and Nick Jennings},
url = {http://eprints.soton.ac.uk/272478/},
year = {2011},
date = {2011-01-01},
booktitle = {Third Human Computation Workshop},
keywords = {Disaster Management, human-agent interaction, mas, multi-agent systems},
pubstate = {published},
tppubtype = {inproceedings}
}
Voice, Thomas; Vytelingum, Perukrishnen; Ramchurn, Sarvapali; Rogers, Alex; Jennings, Nick
Decentralised Control of Micro-Storage in the Smart Grid Proceedings Article
In: AAAI-11: Twenty-Fifth Conference on Artificial Intelligence, pp. 1421–1426, 2011, (Event Dates: August 7?11, 2011).
Abstract | Links | BibTeX | Tags: electricity, Energy, smart grid
@inproceedings{eps272262,
title = {Decentralised Control of Micro-Storage in the Smart Grid},
author = {Thomas Voice and Perukrishnen Vytelingum and Sarvapali Ramchurn and Alex Rogers and Nick Jennings},
url = {http://eprints.soton.ac.uk/272262/},
year = {2011},
date = {2011-01-01},
booktitle = {AAAI-11: Twenty-Fifth Conference on Artificial Intelligence},
pages = {1421–1426},
abstract = {In this paper, we propose a novel decentralised control mechanism to manage micro-storage in the smart grid. Our approach uses an adaptive pricing scheme that energy suppliers apply to home smart agents controlling micro-storage devices. In particular, we prove that the interaction between a supplier using our pricing scheme and the actions of selfish micro-storage agents forms a globally stable feedback loop that converges to an efficient equilibrium. We further propose a market strategy that allows the supplier to reduce wholesale purchasing costs without increasing the uncertainty and variance for its aggregate consumer demand. Moreover, we empirically evaluate our mechanism (based on the UK grid data) and show that it yields savings of up to 16% in energy cost for consumers using storage devices with average capacity 10 kWh. Furthermore, we show that it is robust against extreme system changes.},
note = {Event Dates: August 7?11, 2011},
keywords = {electricity, Energy, smart grid},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, we propose a novel decentralised control mechanism to manage micro-storage in the smart grid. Our approach uses an adaptive pricing scheme that energy suppliers apply to home smart agents controlling micro-storage devices. In particular, we prove that the interaction between a supplier using our pricing scheme and the actions of selfish micro-storage agents forms a globally stable feedback loop that converges to an efficient equilibrium. We further propose a market strategy that allows the supplier to reduce wholesale purchasing costs without increasing the uncertainty and variance for its aggregate consumer demand. Moreover, we empirically evaluate our mechanism (based on the UK grid data) and show that it yields savings of up to 16% in energy cost for consumers using storage devices with average capacity 10 kWh. Furthermore, we show that it is robust against extreme system changes.
Vytelingum, Perukrishnen; Voice, Thomas; Ramchurn, Sarvapali; Rogers, Alex; Jennings, Nick
Theoretical and practical foundations of large-scale agent-based micro-storage in the smart grid Journal Article
In: Journal of Artificial Intelligence Research, vol. 42, pp. 765–813, 2011, (AAMAS 2010 iRobot Best Paper Award).
Abstract | Links | BibTeX | Tags: agents, Energy, mas, multi-agent systems, provenance
@article{eps272961,
title = {Theoretical and practical foundations of large-scale agent-based micro-storage in the smart grid},
author = {Perukrishnen Vytelingum and Thomas Voice and Sarvapali Ramchurn and Alex Rogers and Nick Jennings},
url = {http://eprints.soton.ac.uk/272961/},
year = {2011},
date = {2011-01-01},
journal = {Journal of Artificial Intelligence Research},
volume = {42},
pages = {765–813},
abstract = {In this paper, we present a novel decentralised management technique that allows electricity micro-storage devices, deployed within individual homes as part of a smart electricity grid, to converge to profitable and efficient behaviours. Specifically, we propose the use of software agents, residing on the users' smart meters, to automate and optimise the charging cycle of micro-storage devices in the home to minimise its costs, and we present a study of both the theoretical underpinnings and the implications of a practical solution, of using software agents for such micro-storage management. First, by formalising the strategic choice each agent makes in deciding when to charge its battery, we develop a game-theoretic framework within which we can analyse the competitive equilibria of an electricity grid populated by such agents and hence predict the best consumption profile for that population given their battery properties and individual load profiles. Our framework also allows us to compute theoretical bounds on the amount of storage that will be adopted by the population. Second, to analyse the practical implications of micro-storage deployments in the grid, we present a novel algorithm that each agent can use to optimise its battery storage profile in order to minimise its owner's costs. This algorithm uses a learning strategy that allows it to adapt as the price of electricity changes in real-time, and we show that the adoption of these strategies results in the system converging to the theoretical equilibria. Finally, we empirically evaluate the adoption of our micro-storage management technique within a complex setting, based on the UK electricity market, where agents may have widely varying load profiles, battery types, and learning rates. In this case, our approach yields savings of up to 14% in energy cost for an average consumer using a storage device with a capacity of less than 4.5 kWh and up to a 7% reduction in carbon emissions resulting from electricity generation (with only domestic consumers adopting micro-storage and, commercial and industrial consumers not changing their demand). Moreover, corroborating our theoretical bound, an equilibrium is shown to exist where no more than 48% of households would wish to own storage devices and where social welfare would also be improved (yielding overall annual savings of nearly pounds1.5B).},
note = {AAMAS 2010 iRobot Best Paper Award},
keywords = {agents, Energy, mas, multi-agent systems, provenance},
pubstate = {published},
tppubtype = {article}
}
In this paper, we present a novel decentralised management technique that allows electricity micro-storage devices, deployed within individual homes as part of a smart electricity grid, to converge to profitable and efficient behaviours. Specifically, we propose the use of software agents, residing on the users' smart meters, to automate and optimise the charging cycle of micro-storage devices in the home to minimise its costs, and we present a study of both the theoretical underpinnings and the implications of a practical solution, of using software agents for such micro-storage management. First, by formalising the strategic choice each agent makes in deciding when to charge its battery, we develop a game-theoretic framework within which we can analyse the competitive equilibria of an electricity grid populated by such agents and hence predict the best consumption profile for that population given their battery properties and individual load profiles. Our framework also allows us to compute theoretical bounds on the amount of storage that will be adopted by the population. Second, to analyse the practical implications of micro-storage deployments in the grid, we present a novel algorithm that each agent can use to optimise its battery storage profile in order to minimise its owner's costs. This algorithm uses a learning strategy that allows it to adapt as the price of electricity changes in real-time, and we show that the adoption of these strategies results in the system converging to the theoretical equilibria. Finally, we empirically evaluate the adoption of our micro-storage management technique within a complex setting, based on the UK electricity market, where agents may have widely varying load profiles, battery types, and learning rates. In this case, our approach yields savings of up to 14% in energy cost for an average consumer using a storage device with a capacity of less than 4.5 kWh and up to a 7% reduction in carbon emissions resulting from electricity generation (with only domestic consumers adopting micro-storage and, commercial and industrial consumers not changing their demand). Moreover, corroborating our theoretical bound, an equilibrium is shown to exist where no more than 48% of households would wish to own storage devices and where social welfare would also be improved (yielding overall annual savings of nearly pounds1.5B).
2010
Macarthur, Kathryn; Farinelli, Alessandro; Ramchurn, Sarvapali; Jennings, Nick
Efficient, Superstabilizing Decentralised Optimisation for Dynamic Task Allocation Environments Proceedings Article
In: Third International Workshop on: Optimisation in Multi-Agent Systems (OptMas) at the Ninth Joint Conference on Autonomous and Multi-Agent Systems, pp. 25–32, 2010, (Event Dates: 10 May 2010).
Abstract | Links | BibTeX | Tags: agents, Disaster Management, mas, Multi-agent scheduling, multi-agent systems
@inproceedings{eps268588,
title = {Efficient, Superstabilizing Decentralised Optimisation for Dynamic Task Allocation Environments},
author = {Kathryn Macarthur and Alessandro Farinelli and Sarvapali Ramchurn and Nick Jennings},
url = {http://eprints.soton.ac.uk/268588/},
year = {2010},
date = {2010-01-01},
booktitle = {Third International Workshop on: Optimisation in Multi-Agent Systems (OptMas) at the Ninth Joint Conference on Autonomous and Multi-Agent Systems},
pages = {25–32},
abstract = {Decentralised optimisation is a key issue for multi-agent systems, and while many solution techniques have been developed, few provide support for dynamic environments, which change over time, such as disaster management. Given this, in this paper, we present Bounded Fast Max Sum (BFMS): a novel, dynamic, superstabilizing algorithm which provides a bounded approximate solution to certain classes of distributed constraint optimisation problems. We achieve this by eliminating dependencies in the constraint functions, according to how much impact they have on the overall solution value. In more detail, we propose iGHS, which computes a maximum spanning tree on subsections of the constraint graph, in order to reduce communication and computation overheads. Given this, we empirically evaluate BFMS, which shows that BFMS reduces communication and computation done by Bounded Max Sum by up to 99%, while obtaining 60-88% of the optimal utility.},
note = {Event Dates: 10 May 2010},
keywords = {agents, Disaster Management, mas, Multi-agent scheduling, multi-agent systems},
pubstate = {published},
tppubtype = {inproceedings}
}
Decentralised optimisation is a key issue for multi-agent systems, and while many solution techniques have been developed, few provide support for dynamic environments, which change over time, such as disaster management. Given this, in this paper, we present Bounded Fast Max Sum (BFMS): a novel, dynamic, superstabilizing algorithm which provides a bounded approximate solution to certain classes of distributed constraint optimisation problems. We achieve this by eliminating dependencies in the constraint functions, according to how much impact they have on the overall solution value. In more detail, we propose iGHS, which computes a maximum spanning tree on subsections of the constraint graph, in order to reduce communication and computation overheads. Given this, we empirically evaluate BFMS, which shows that BFMS reduces communication and computation done by Bounded Max Sum by up to 99%, while obtaining 60-88% of the optimal utility.
Ramchurn, S. D.; Polukarov, Mariya; Farinelli, Alessandro; Jennings, Nick; Trong, Cuong
Coalition Formation with Spatial and Temporal Constraints Proceedings Article
In: International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2010), pp. 1181–1188, 2010, (Event Dates: May 2010).
Abstract | Links | BibTeX | Tags: agents, Coalition Formation, Disaster Management, Multi-agent scheduling, RoboCup Rescue
@inproceedings{eps268497,
title = {Coalition Formation with Spatial and Temporal Constraints},
author = {S. D. Ramchurn and Mariya Polukarov and Alessandro Farinelli and Nick Jennings and Cuong Trong},
url = {http://eprints.soton.ac.uk/268497/},
year = {2010},
date = {2010-01-01},
booktitle = {International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2010)},
pages = {1181–1188},
abstract = {The coordination of emergency responders and robots to undertake a number of tasks in disaster scenarios is a grand challenge for multi-agent systems. Central to this endeavour is the problem of forming the best teams (coalitions) of responders to perform the various tasks in the area where the disaster has struck. Moreover, these teams may have to form, disband, and reform in different areas of the disaster region. This is because in most cases there will be more tasks than agents. Hence, agents need to schedule themselves to attempt each task in turn. Second, the tasks themselves can be very complex: requiring the agents to work on them for different lengths of time and having deadlines by when they need to be completed. The problem is complicated still further when different coalitions perform tasks with different levels of efficiency. Given all these facets, we define this as The Coalition Formation with Spatial and Temporal constraints problem (CFSTP).We show that this problem is NP-hard–in particular, it contains the wellknown complex combinatorial problem of Team Orienteering as a special case. Based on this, we design a Mixed Integer Program to optimally solve small-scale instances of the CFSTP and develop new anytime heuristics that can, on average, complete 97% of the tasks for large problems (20 agents and 300 tasks). In so doing, our solutions represent the first results for CFSTP.},
note = {Event Dates: May 2010},
keywords = {agents, Coalition Formation, Disaster Management, Multi-agent scheduling, RoboCup Rescue},
pubstate = {published},
tppubtype = {inproceedings}
}
The coordination of emergency responders and robots to undertake a number of tasks in disaster scenarios is a grand challenge for multi-agent systems. Central to this endeavour is the problem of forming the best teams (coalitions) of responders to perform the various tasks in the area where the disaster has struck. Moreover, these teams may have to form, disband, and reform in different areas of the disaster region. This is because in most cases there will be more tasks than agents. Hence, agents need to schedule themselves to attempt each task in turn. Second, the tasks themselves can be very complex: requiring the agents to work on them for different lengths of time and having deadlines by when they need to be completed. The problem is complicated still further when different coalitions perform tasks with different levels of efficiency. Given all these facets, we define this as The Coalition Formation with Spatial and Temporal constraints problem (CFSTP).We show that this problem is NP-hard–in particular, it contains the wellknown complex combinatorial problem of Team Orienteering as a special case. Based on this, we design a Mixed Integer Program to optimally solve small-scale instances of the CFSTP and develop new anytime heuristics that can, on average, complete 97% of the tasks for large problems (20 agents and 300 tasks). In so doing, our solutions represent the first results for CFSTP.
Ramchurn, Sarvapali; Farinelli, Alessandro; Macarthur, Kathryn; Polukarov, Mariya; Jennings, Nick
Decentralised Coordination in RoboCup Rescue Journal Article
In: The Computer Journal, vol. 53, no. 9, pp. 1–15, 2010.
Abstract | Links | BibTeX | Tags: Disaster Management, mas, Multi-agent scheduling, multi-agent systems
@article{eps268499,
title = {Decentralised Coordination in RoboCup Rescue},
author = {Sarvapali Ramchurn and Alessandro Farinelli and Kathryn Macarthur and Mariya Polukarov and Nick Jennings},
url = {http://eprints.soton.ac.uk/268499/},
year = {2010},
date = {2010-01-01},
journal = {The Computer Journal},
volume = {53},
number = {9},
pages = {1–15},
publisher = {Oxford Journals},
abstract = {Emergency responders are faced with a number of significant challenges when managing major disasters. First, the number of rescue tasks posed is usually larger than the number of responders (or agents) and the resources available to them. Second, each task is likely to require a different level of effort in order to be completed by its deadline. Third, new tasks may continually appear or disappear from the environment, thus requiring the responders to quickly recompute their allocation of resources. Fourth, forming teams or coalitions of multiple agents from different agencies is vital since no single agency will have all the resources needed to save victims, unblock roads, and extinguish the ?res which might erupt in the disaster space. Given this, coalitions have to be efficiently selected and scheduled to work across the disaster space so as to maximise the number of lives and the portion of the infrastructure saved. In particular, it is important that the selection of such coalitions should be performed in a decentralised fashion in order to avoid a single point of failure in the system. Moreover, it is critical that responders communicate only locally given they are likely to have limited battery power or minimal access to long range communication devices. Against this background, we provide a novel decentralised solution to the coalition formation process that pervades disaster management. More specifically, we model the emergency management scenario defined in the RoboCup Rescue disaster simulation platform as a Coalition Formation with Spatial and Temporal constraints (CFST) problem where agents form coalitions in order to complete tasks, each with different demands. In order to design a decentralised algorithm for CFST we formulate it as a Distributed Constraint Optimisation problem and show how to solve it using the state-of-the-art Max-Sum algorithm that provides a completely decentralised message-passing solution. We then provide a novel algorithm (F-Max-Sum) that avoids sending redundant messages and efficiently adapts to changes in the environment. In empirical evaluations, our algorithm is shown to generate better solutions than other decentralised algorithms used for this problem.},
keywords = {Disaster Management, mas, Multi-agent scheduling, multi-agent systems},
pubstate = {published},
tppubtype = {article}
}
Emergency responders are faced with a number of significant challenges when managing major disasters. First, the number of rescue tasks posed is usually larger than the number of responders (or agents) and the resources available to them. Second, each task is likely to require a different level of effort in order to be completed by its deadline. Third, new tasks may continually appear or disappear from the environment, thus requiring the responders to quickly recompute their allocation of resources. Fourth, forming teams or coalitions of multiple agents from different agencies is vital since no single agency will have all the resources needed to save victims, unblock roads, and extinguish the ?res which might erupt in the disaster space. Given this, coalitions have to be efficiently selected and scheduled to work across the disaster space so as to maximise the number of lives and the portion of the infrastructure saved. In particular, it is important that the selection of such coalitions should be performed in a decentralised fashion in order to avoid a single point of failure in the system. Moreover, it is critical that responders communicate only locally given they are likely to have limited battery power or minimal access to long range communication devices. Against this background, we provide a novel decentralised solution to the coalition formation process that pervades disaster management. More specifically, we model the emergency management scenario defined in the RoboCup Rescue disaster simulation platform as a Coalition Formation with Spatial and Temporal constraints (CFST) problem where agents form coalitions in order to complete tasks, each with different demands. In order to design a decentralised algorithm for CFST we formulate it as a Distributed Constraint Optimisation problem and show how to solve it using the state-of-the-art Max-Sum algorithm that provides a completely decentralised message-passing solution. We then provide a novel algorithm (F-Max-Sum) that avoids sending redundant messages and efficiently adapts to changes in the environment. In empirical evaluations, our algorithm is shown to generate better solutions than other decentralised algorithms used for this problem.
Vytelingum, Perukrishnen; Ramchurn, Sarvapali D.; Voice, Thomas D.; Rogers, Alex; Jennings, Nicholas R.
Trading agents for the smart electricity grid Proceedings Article
In: The Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), pp. 897–904, 2010, (Event Dates: May 10-14, 2010).
Abstract | Links | BibTeX | Tags: agents, balancing mechanism, continuous double auction, Energy, markets, smart grid
@inproceedings{eps268361,
title = {Trading agents for the smart electricity grid},
author = {Perukrishnen Vytelingum and Sarvapali D. Ramchurn and Thomas D. Voice and Alex Rogers and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/268361/},
year = {2010},
date = {2010-01-01},
booktitle = {The Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010)},
pages = {897–904},
abstract = {The vision of the Smart Grid includes the creation of intelligent electricity supply networks to allow efficient use of energy resources, reduce carbon emissions and are robust to failures. One of the key assumptions underlying this vision is that it will be possible to manage the trading of electricity between homes and micro-grids while coping with the inherent real-time dynamism in electricity demand and supply. The management of these trades needs to take into account the fact that most, if not all, of the actors in the system are self-interested and transmission line capacities are constrained. Against this background, we develop and evaluate a novel market-based mechanism and novel trading strategies for the Smart Grid. Our mechanism is based on the Continuous Double Auction (CDA) and automatically manages the congestion within the system by pricing the flow of electricity. We also introduce mechanisms to ensure the system can cope with unforeseen demand or increased supply capacity in real time. Finally, we develop new strategies that we show achieve high market efficiency (typically over 90%).},
note = {Event Dates: May 10-14, 2010},
keywords = {agents, balancing mechanism, continuous double auction, Energy, markets, smart grid},
pubstate = {published},
tppubtype = {inproceedings}
}
The vision of the Smart Grid includes the creation of intelligent electricity supply networks to allow efficient use of energy resources, reduce carbon emissions and are robust to failures. One of the key assumptions underlying this vision is that it will be possible to manage the trading of electricity between homes and micro-grids while coping with the inherent real-time dynamism in electricity demand and supply. The management of these trades needs to take into account the fact that most, if not all, of the actors in the system are self-interested and transmission line capacities are constrained. Against this background, we develop and evaluate a novel market-based mechanism and novel trading strategies for the Smart Grid. Our mechanism is based on the Continuous Double Auction (CDA) and automatically manages the congestion within the system by pricing the flow of electricity. We also introduce mechanisms to ensure the system can cope with unforeseen demand or increased supply capacity in real time. Finally, we develop new strategies that we show achieve high market efficiency (typically over 90%).
Vytelingum, Perukrishnen; Voice, Thomas D.; Ramchurn, Sarvapali D.; Rogers, Alex; Jennings, Nicholas R.
Agent-Based Micro-Storage Management for the Smart Grid Proceedings Article
In: The Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010) - Won the Best Paper Award, pp. 39–46, 2010, (Winner of the Best Paper Award Event Dates: May 10-14, 2010).
Abstract | Links | BibTeX | Tags: agent-based modelling, agents, Energy, game-theory, smart grid
@inproceedings{eps268360,
title = {Agent-Based Micro-Storage Management for the Smart Grid},
author = {Perukrishnen Vytelingum and Thomas D. Voice and Sarvapali D. Ramchurn and Alex Rogers and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/268360/},
year = {2010},
date = {2010-01-01},
booktitle = {The Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010) - Won the Best Paper Award},
pages = {39–46},
abstract = {The use of energy storage devices in homes has been advocated as one of the main ways of saving energy and reducing the reliance on fossil fuels in the future Smart Grid. However, if micro-storage devices are all charged at the same time using power from the electricity grid, it means a higher demand and, hence, more generation capacity, more carbon emissions, and, in the worst case, breaking down the system due to over-demand. To alleviate such issues, in this paper, we present a novel agent-based micro-storage management technique that allows all (individually-owned) storage devices in the system to converge to profitable, efficient behaviour. Specifically, we provide a general framework within which to analyse the Nash equilibrium of an electricity grid and devise new agent-based storage learning strategies that adapt to market conditions. Taken altogether, our solution shows that, specifically, in the UK electricity market, it is possible to achieve savings of up to 13% on average for a consumer on his electricity bill with a storage device of 4 kWh. Moreover, we show that there exists an equilibrium where only 38% of UK households would own storage devices and where social welfare would be also maximised (with an overall annual savings of nearly GBP 1.5B at that equilibrium).},
note = {Winner of the Best Paper Award Event Dates: May 10-14, 2010},
keywords = {agent-based modelling, agents, Energy, game-theory, smart grid},
pubstate = {published},
tppubtype = {inproceedings}
}
The use of energy storage devices in homes has been advocated as one of the main ways of saving energy and reducing the reliance on fossil fuels in the future Smart Grid. However, if micro-storage devices are all charged at the same time using power from the electricity grid, it means a higher demand and, hence, more generation capacity, more carbon emissions, and, in the worst case, breaking down the system due to over-demand. To alleviate such issues, in this paper, we present a novel agent-based micro-storage management technique that allows all (individually-owned) storage devices in the system to converge to profitable, efficient behaviour. Specifically, we provide a general framework within which to analyse the Nash equilibrium of an electricity grid and devise new agent-based storage learning strategies that adapt to market conditions. Taken altogether, our solution shows that, specifically, in the UK electricity market, it is possible to achieve savings of up to 13% on average for a consumer on his electricity bill with a storage device of 4 kWh. Moreover, we show that there exists an equilibrium where only 38% of UK households would own storage devices and where social welfare would be also maximised (with an overall annual savings of nearly GBP 1.5B at that equilibrium).
2009
Rahwan, Talal; Ramchurn, Sarvapali; Jennings, Nicholas; Giovannucci, Andrea
An anytime algorithm for optimal coalition structure generation Journal Article
In: Journal of Artificial Intelligence Research, vol. 34, pp. 521–567, 2009.
Abstract | Links | BibTeX | Tags: Coalition Formation, multi-agent systems
@article{eps267179,
title = {An anytime algorithm for optimal coalition structure generation},
author = {Talal Rahwan and Sarvapali Ramchurn and Nicholas Jennings and Andrea Giovannucci},
url = {http://eprints.soton.ac.uk/267179/},
year = {2009},
date = {2009-01-01},
journal = {Journal of Artificial Intelligence Research},
volume = {34},
pages = {521–567},
abstract = {Coalition formation is a fundamental type of interaction that involves the creation of coherent groupings of distinct, autonomous, agents in order to efficiently achieve their individual or collective goals. Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining which of the many possible coalitions to form in order to achieve some goal. This usually requires calculating a value for every possible coalition, known as the coalition value, which indicates how beneficial that coalition would be if it was formed. Once these values are calculated, the agents usually need to find a combination of coalitions, in which every agent belongs to exactly one coalition, and by which the overall outcome of the system is maximized. However, this coalition structure generation problem is extremely challenging due to the number of possible solutions that need to be examined, which grows exponentially with the number of agents involved. To date, therefore, many algorithms have been proposed to solve this problem using different techniques–ranging from dynamic programming, to integer programming, to stochastic search – all of which suffer from major limitations relating to execution time, solution quality, and memory requirements. With this in mind, we develop an anytime algorithm to solve the coalition structure generation problem. Specifically, the algorithm uses a novel representation of the search space, which partitions the space of possible solutions into sub-spaces such that it is possible to compute upper and lower bounds on the values of the best coalition structures in them. These bounds are then used to identify the sub-spaces that have no potential of containing the optimal solution so that they can be pruned. The algorithm, then, searches through the remaining sub-spaces very efficiently using a branch-and-bound technique to avoid examining all the solutions within the searched subspace(s). In this setting, we prove that our algorithm enumerates all coalition structures efficiently by avoiding redundant and invalid solutions automatically. Moreover, in order to effectively test our algorithm we develop a new type of input distribution which allows us to generate more reliable benchmarks compared to the input distributions previously used in the field. Given this new distribution, we show that for 27 agents our algorithm is able to find solutions that are optimal in 0:175% of the time required by the fastest available algorithm in the literature. The algorithm is anytime, and if interrupted before it would have normally terminated, it can still provide a solution that is guaranteed to be within a bound from the optimal one. Moreover, the guarantees we provide on the quality of the solution are significantly better than those provided by the previous state of the art algorithms designed for this purpose. For example, for the worst case distribution given 25 agents, our algorithm is able to find a 90% efficient solution in around 10% of time it takes to find the optimal solution.},
keywords = {Coalition Formation, multi-agent systems},
pubstate = {published},
tppubtype = {article}
}
Coalition formation is a fundamental type of interaction that involves the creation of coherent groupings of distinct, autonomous, agents in order to efficiently achieve their individual or collective goals. Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining which of the many possible coalitions to form in order to achieve some goal. This usually requires calculating a value for every possible coalition, known as the coalition value, which indicates how beneficial that coalition would be if it was formed. Once these values are calculated, the agents usually need to find a combination of coalitions, in which every agent belongs to exactly one coalition, and by which the overall outcome of the system is maximized. However, this coalition structure generation problem is extremely challenging due to the number of possible solutions that need to be examined, which grows exponentially with the number of agents involved. To date, therefore, many algorithms have been proposed to solve this problem using different techniques–ranging from dynamic programming, to integer programming, to stochastic search – all of which suffer from major limitations relating to execution time, solution quality, and memory requirements. With this in mind, we develop an anytime algorithm to solve the coalition structure generation problem. Specifically, the algorithm uses a novel representation of the search space, which partitions the space of possible solutions into sub-spaces such that it is possible to compute upper and lower bounds on the values of the best coalition structures in them. These bounds are then used to identify the sub-spaces that have no potential of containing the optimal solution so that they can be pruned. The algorithm, then, searches through the remaining sub-spaces very efficiently using a branch-and-bound technique to avoid examining all the solutions within the searched subspace(s). In this setting, we prove that our algorithm enumerates all coalition structures efficiently by avoiding redundant and invalid solutions automatically. Moreover, in order to effectively test our algorithm we develop a new type of input distribution which allows us to generate more reliable benchmarks compared to the input distributions previously used in the field. Given this new distribution, we show that for 27 agents our algorithm is able to find solutions that are optimal in 0:175% of the time required by the fastest available algorithm in the literature. The algorithm is anytime, and if interrupted before it would have normally terminated, it can still provide a solution that is guaranteed to be within a bound from the optimal one. Moreover, the guarantees we provide on the quality of the solution are significantly better than those provided by the previous state of the art algorithms designed for this purpose. For example, for the worst case distribution given 25 agents, our algorithm is able to find a 90% efficient solution in around 10% of time it takes to find the optimal solution.
Ramchurn, Sarvapali D.; Mezzetti, Claudio; Giovannucci, Andrea; Rodriguez, Juan A.; Dash, Rajdeep K.; Jennings, Nicholas R.
Trust-based mechanisms for robust and efficient task allocation in the presence of execution uncertainty Journal Article
In: Journal of Artificial Intelligence Research, vol. 35, pp. 1–41, 2009.
Abstract | Links | BibTeX | Tags: mechanism design, optimisation, Trust, uncertainty
@article{eps267288,
title = {Trust-based mechanisms for robust and efficient task allocation in the presence of execution uncertainty},
author = {Sarvapali D. Ramchurn and Claudio Mezzetti and Andrea Giovannucci and Juan A. Rodriguez and Rajdeep K. Dash and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/267288/},
year = {2009},
date = {2009-01-01},
journal = {Journal of Artificial Intelligence Research},
volume = {35},
pages = {1–41},
abstract = {Vickrey-Clarke-Groves (VCG) mechanisms are often used to allocate tasks to selfish and rational agents. VCG mechanisms are incentive-compatible, direct mechanisms that are efficient (i.e. maximise social utility) and individually rational (i.e. agents prefer to join rather than opt out). However, an important assumption of these mechanisms is that the agents will always successfully complete their allocated tasks. Clearly, this assumption is unrealistic in many real-world applications where agents can, and often do, fail in their endeavours. Moreover, whether an agent is deemed to have failed may be perceived differently by different agents. Such subjective perceptions about an agent's probability of succeeding at a given task are often captured and reasoned about using the notion of trust. Given this background, in this paper we investigate the design of novel mechanisms that take into account the trust between agents when allocating tasks. Specifically, we develop a new class of mechanisms, called trust-based mechanisms, that can take into account multiple subjective measures of the probability of an agent succeeding at a given task and produce allocations that maximise social utility, whilst ensuring that no agent obtains a negative utility. We then show that such mechanisms pose a challenging new combinatorial optimisation problem (that is NP-complete), devise a novel representation for solving the problem, and develop an effective integer programming solution (that can solve instances with about 2x10^ 5 possible allocations in 40 seconds).},
keywords = {mechanism design, optimisation, Trust, uncertainty},
pubstate = {published},
tppubtype = {article}
}
Vickrey-Clarke-Groves (VCG) mechanisms are often used to allocate tasks to selfish and rational agents. VCG mechanisms are incentive-compatible, direct mechanisms that are efficient (i.e. maximise social utility) and individually rational (i.e. agents prefer to join rather than opt out). However, an important assumption of these mechanisms is that the agents will always successfully complete their allocated tasks. Clearly, this assumption is unrealistic in many real-world applications where agents can, and often do, fail in their endeavours. Moreover, whether an agent is deemed to have failed may be perceived differently by different agents. Such subjective perceptions about an agent's probability of succeeding at a given task are often captured and reasoned about using the notion of trust. Given this background, in this paper we investigate the design of novel mechanisms that take into account the trust between agents when allocating tasks. Specifically, we develop a new class of mechanisms, called trust-based mechanisms, that can take into account multiple subjective measures of the probability of an agent succeeding at a given task and produce allocations that maximise social utility, whilst ensuring that no agent obtains a negative utility. We then show that such mechanisms pose a challenging new combinatorial optimisation problem (that is NP-complete), devise a novel representation for solving the problem, and develop an effective integer programming solution (that can solve instances with about 2x10^ 5 possible allocations in 40 seconds).
Valkenhoef, Gert; Ramchurn, Sarvapali D.; Vytelingum, Perukrishnen; Jennings, Nicholas R.; Verbrugge, Rinek
Continuous double auctions with execution uncertainty Proceedings Article
In: Workshop on Trading Agent Design and Analysis (TADA-09), 2009.
Abstract | Links | BibTeX | Tags:
@inproceedings{eps267329,
title = {Continuous double auctions with execution uncertainty},
author = {Gert Valkenhoef and Sarvapali D. Ramchurn and Perukrishnen Vytelingum and Nicholas R. Jennings and Rinek Verbrugge},
url = {http://eprints.soton.ac.uk/267329/},
year = {2009},
date = {2009-01-01},
booktitle = {Workshop on Trading Agent Design and Analysis (TADA-09)},
abstract = {We propose a novel variant of the Continuous Double Auction (CDA), the Trust-based CDA (T-CDA), which we demonstrate to be robust to execution uncertainty. This is desirable in a setting where traders may fail to deliver the goods, services or payments they have promised. Specifically, the TCDA provides a mechanism that allows agents to commit to trades they believe will maximize their expected utility. In this paper, we consider agents that use their trust in other agents to estimate the expected utility of a transaction. We empirically evaluate the mechanism, both against the optimal solution given perfect and complete information and against the standard CDA.We show that the T-CDA consistently outperforms the traditional CDA as execution uncertainty increases in the system. Furthermore, we investigate the robustness of the mechanism to unreliable trust information and find that performance degrades gracefully as information quality decreases.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We propose a novel variant of the Continuous Double Auction (CDA), the Trust-based CDA (T-CDA), which we demonstrate to be robust to execution uncertainty. This is desirable in a setting where traders may fail to deliver the goods, services or payments they have promised. Specifically, the TCDA provides a mechanism that allows agents to commit to trades they believe will maximize their expected utility. In this paper, we consider agents that use their trust in other agents to estimate the expected utility of a transaction. We empirically evaluate the mechanism, both against the optimal solution given perfect and complete information and against the standard CDA.We show that the T-CDA consistently outperforms the traditional CDA as execution uncertainty increases in the system. Furthermore, we investigate the robustness of the mechanism to unreliable trust information and find that performance degrades gracefully as information quality decreases.
2008
Adams, Niall; Field, Martin; Gelenbe, Erol; Hand, David; Jennings, Nicholas; Leslie, David; Nicholson, David; Ramchurn, Sarvapali; Rogers, Alex
Intelligent Agents for Disaster Management Proceedings Article
In: Proceedings of the IARP/EURON Workshop on Robotics for Risky Interventions and Environmental Surveillance (RISE), 2008.
Abstract | Links | BibTeX | Tags:
@inproceedings{eps272011,
title = {Intelligent Agents for Disaster Management},
author = {Niall Adams and Martin Field and Erol Gelenbe and David Hand and Nicholas Jennings and David Leslie and David Nicholson and Sarvapali Ramchurn and Alex Rogers},
url = {http://eprints.soton.ac.uk/272011/},
year = {2008},
date = {2008-01-01},
booktitle = {Proceedings of the IARP/EURON Workshop on Robotics for Risky Interventions and Environmental Surveillance (RISE)},
abstract = {ALADDIN [1] is a multi-disciplinary project that is developing novel techniques, architectures, and mechanisms for multi-agent systems in uncertain and dynamic environments. The application focus of the project is disaster management. Research within a number of themes is being pursued and this is considering different aspects of the interaction between autonomous agents and the decentralised system architectures that support those interactions. The aim of the research is to contribute to building more robust multi-agent systems for future applications in disaster management and other similar domains.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
ALADDIN [1] is a multi-disciplinary project that is developing novel techniques, architectures, and mechanisms for multi-agent systems in uncertain and dynamic environments. The application focus of the project is disaster management. Research within a number of themes is being pursued and this is considering different aspects of the interaction between autonomous agents and the decentralised system architectures that support those interactions. The aim of the research is to contribute to building more robust multi-agent systems for future applications in disaster management and other similar domains.
Osborne, Michael A; Rogers, Alex; Ramchurn, Sarvapali; Roberts, Stephen J; Jennings, N. R.
Towards Real-Time Information Processing of Sensor Network Data using Computationally Efficient Multi-output Gaussian Processes Proceedings Article
In: International Conference on Information Processing in Sensor Networks (IPSN 2008), pp. 109–120, 2008, (Event Dates: April 2008).
Abstract | Links | BibTeX | Tags:
@inproceedings{eps265122,
title = {Towards Real-Time Information Processing of Sensor Network Data using Computationally Efficient Multi-output Gaussian Processes},
author = {Michael A Osborne and Alex Rogers and Sarvapali Ramchurn and Stephen J Roberts and N. R. Jennings},
url = {http://eprints.soton.ac.uk/265122/},
year = {2008},
date = {2008-01-01},
booktitle = {International Conference on Information Processing in Sensor Networks (IPSN 2008)},
pages = {109–120},
abstract = {In this paper, we describe a novel, computationally efficient algorithm that facilitates the autonomous acquisition of readings from sensor networks (deciding when and which sensor to acquire readings from at any time), and which can, with minimal domain knowledge, perform a range of information processing tasks including modelling the accuracy of the sensor readings, predicting the value of missing sensor readings, and predicting how the monitored environmental variables will evolve into the future. Our motivating scenario is the need to provide situational awareness support to first responders at the scene of a large scale incident, and to this end, we describe a novel iterative formulation of a multi-output Gaussian process that can build and exploit a probabilistic model of the environmental variables being measured (including the correlations and delays that exist between them). We validate our approach using data collected from a network of weather sensors located on the south coast of England.},
note = {Event Dates: April 2008},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, we describe a novel, computationally efficient algorithm that facilitates the autonomous acquisition of readings from sensor networks (deciding when and which sensor to acquire readings from at any time), and which can, with minimal domain knowledge, perform a range of information processing tasks including modelling the accuracy of the sensor readings, predicting the value of missing sensor readings, and predicting how the monitored environmental variables will evolve into the future. Our motivating scenario is the need to provide situational awareness support to first responders at the scene of a large scale incident, and to this end, we describe a novel iterative formulation of a multi-output Gaussian process that can build and exploit a probabilistic model of the environmental variables being measured (including the correlations and delays that exist between them). We validate our approach using data collected from a network of weather sensors located on the south coast of England.
Rogers, Alex; Osborne, Michael A; Ramchurn, Sarvapali; Roberts, Stephen J; Jennings, N. R.
Information Agents for Pervasive Sensor Networks Proceedings Article
In: Sixth Annual IEEE International Conference on Pervasive Computing and Communications (PerCom 2008), pp. 294–299, 2008, (Event Dates: March 2008).
Abstract | Links | BibTeX | Tags:
@inproceedings{eps264967,
title = {Information Agents for Pervasive Sensor Networks},
author = {Alex Rogers and Michael A Osborne and Sarvapali Ramchurn and Stephen J Roberts and N. R. Jennings},
url = {http://eprints.soton.ac.uk/264967/},
year = {2008},
date = {2008-01-01},
booktitle = {Sixth Annual IEEE International Conference on Pervasive Computing and Communications (PerCom 2008)},
pages = {294–299},
abstract = {In this paper, we describe an information agent, that resides on a mobile computer or personal digital assistant (PDA), that can autonomously acquire sensor readings from pervasive sensor networks (deciding when and which sensor to acquire readings from at any time). Moreover, it can perform a range of information processing tasks including modelling the accuracy of the sensor readings, predicting the value of missing sensor readings, and predicting how the monitored environmental parameters will evolve into the future. Our motivating scenario is the need to provide situational awareness support to first responders at the scene of a large scale incident, and we describe how we use an iterative formulation of a multi-output Gaussian process to build a probabilistic model of the environmental parameters being measured by local sensors, and the correlations and delays that exist between them. We validate our approach using data collected from a network of weather sensors located on the south coast of England.},
note = {Event Dates: March 2008},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, we describe an information agent, that resides on a mobile computer or personal digital assistant (PDA), that can autonomously acquire sensor readings from pervasive sensor networks (deciding when and which sensor to acquire readings from at any time). Moreover, it can perform a range of information processing tasks including modelling the accuracy of the sensor readings, predicting the value of missing sensor readings, and predicting how the monitored environmental parameters will evolve into the future. Our motivating scenario is the need to provide situational awareness support to first responders at the scene of a large scale incident, and we describe how we use an iterative formulation of a multi-output Gaussian process to build a probabilistic model of the environmental parameters being measured by local sensors, and the correlations and delays that exist between them. We validate our approach using data collected from a network of weather sensors located on the south coast of England.
2007
Espinoza, Fredrik; Roure, David De; Hamfors, Ola; Hinz, Lucas; Holmberg, Jesper; Jansson, Carl-Gustaf; Jennings, Nick; Luck, Mike; L"onnqvist, Peter; Ramchurn, Sarvapali; Sandin, Anna; Thompson, Mark; Bylund, Markus
Intrusiveness Management for Focused, Efficient, and Enjoyable Activities Book Section
In: The Disappearing Computer: Interaction Design, System Infrastructures and Applications for Smart Environments, pp. 143–160, Springer, 2007.
@incollection{eps265985,
title = {Intrusiveness Management for Focused, Efficient, and Enjoyable Activities},
author = {Fredrik Espinoza and David De Roure and Ola Hamfors and Lucas Hinz and Jesper Holmberg and Carl-Gustaf Jansson and Nick Jennings and Mike Luck and Peter L"onnqvist and Sarvapali Ramchurn and Anna Sandin and Mark Thompson and Markus Bylund},
url = {http://eprints.soton.ac.uk/265985/},
year = {2007},
date = {2007-01-01},
booktitle = {The Disappearing Computer: Interaction Design, System Infrastructures and Applications for Smart Environments},
pages = {143–160},
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Rahwan, T.; Ramchurn, S. D.; Dang, V. D.; Jennings, N. R.
Near-optimal anytime coalition structure generation Proceedings Article
In: 20th International Joint Conference on Artificial Intelligence (IJCAI), pp. 2365–2371, 2007.
Abstract | Links | BibTeX | Tags:
@inproceedings{eps263074,
title = {Near-optimal anytime coalition structure generation},
author = {T. Rahwan and S. D. Ramchurn and V. D. Dang and N. R. Jennings},
url = {http://eprints.soton.ac.uk/263074/},
year = {2007},
date = {2007-01-01},
booktitle = {20th International Joint Conference on Artificial Intelligence (IJCAI)},
pages = {2365–2371},
abstract = {Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best set of agents that should participate in a given team. To this end, in this paper, we present a novel, anytime algorithms designed for this purpose. Our algorithm can generate solutions that either have a tight bound from the optimal or are optimal (depending on the objective) and works by partitioning the space in terms of a small set of elements that represent structures which contain coalitions of particular sizes. It then performs an online heuristic search that prunes the space and only considers valid and non-redundant coalition structures. We empirically show that we are able to find solutions that are, in the worst case, 99% efficient in 0.0043% of the time to find the optimal value by the state of the art dynamic programming (DP) algorithm (for 20 agents), using 33% less memory.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best set of agents that should participate in a given team. To this end, in this paper, we present a novel, anytime algorithms designed for this purpose. Our algorithm can generate solutions that either have a tight bound from the optimal or are optimal (depending on the objective) and works by partitioning the space in terms of a small set of elements that represent structures which contain coalitions of particular sizes. It then performs an online heuristic search that prunes the space and only considers valid and non-redundant coalition structures. We empirically show that we are able to find solutions that are, in the worst case, 99% efficient in 0.0043% of the time to find the optimal value by the state of the art dynamic programming (DP) algorithm (for 20 agents), using 33% less memory.
Rahwan, Talal; Ramchurn, Sarvapali D.; Dang, Viet D.; Giovannucci, Andrea; Jennings, N. R.
Anytime Optimal Coalition Structure Generation Proceedings Article
In: 22nd Conference on Artificial Intelligence (AAAI), pp. 1184–1190, 2007.
Abstract | Links | BibTeX | Tags: Coalition Formation, Coalition Structure Generation, Combinatorial, multi-agent systems, Search, Set Partitioning
@inproceedings{eps263433,
title = {Anytime Optimal Coalition Structure Generation},
author = {Talal Rahwan and Sarvapali D. Ramchurn and Viet D. Dang and Andrea Giovannucci and N. R. Jennings},
url = {http://eprints.soton.ac.uk/263433/},
year = {2007},
date = {2007-01-01},
booktitle = {22nd Conference on Artificial Intelligence (AAAI)},
pages = {1184–1190},
abstract = {Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best groups of agents to select to achieve some goal. To this end, in this paper, we present a novel, optimal anytime algorithm for this coalition structure generation problem that is significantly faster than previous algorithms designed for this purpose. Specifically, our algorithm can generate solutions by partitioning the space of all potential coalitions into sub-spaces that contain coalition structures that are similar, according to some criterion, such that these sub-spaces can be pruned by identifying their bounds. Using this representation, the algorithm then searches through only valid and unique coalition structures and selects the best among them using a branch-and-bound technique. We empirically show that we are able to find solutions that are optimal in 0.082% of the time taken by the state of the art dynamic programming algorithm (for 27 agents) using much less memory (O(2^ n) instead of O(3^ n) for the set of n agents). Moreover, our algorithm is the first to be able to solve the coalition structure generation problem for numbers of agents bigger than 27 in reasonable time (less than 90 minutes for 27 agents as opposed to around 2 months for the best previous solution).},
keywords = {Coalition Formation, Coalition Structure Generation, Combinatorial, multi-agent systems, Search, Set Partitioning},
pubstate = {published},
tppubtype = {inproceedings}
}
Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best groups of agents to select to achieve some goal. To this end, in this paper, we present a novel, optimal anytime algorithm for this coalition structure generation problem that is significantly faster than previous algorithms designed for this purpose. Specifically, our algorithm can generate solutions by partitioning the space of all potential coalitions into sub-spaces that contain coalition structures that are similar, according to some criterion, such that these sub-spaces can be pruned by identifying their bounds. Using this representation, the algorithm then searches through only valid and unique coalition structures and selects the best among them using a branch-and-bound technique. We empirically show that we are able to find solutions that are optimal in 0.082% of the time taken by the state of the art dynamic programming algorithm (for 27 agents) using much less memory (O(2^ n) instead of O(3^ n) for the set of n agents). Moreover, our algorithm is the first to be able to solve the coalition structure generation problem for numbers of agents bigger than 27 in reasonable time (less than 90 minutes for 27 agents as opposed to around 2 months for the best previous solution).
Ramchurn, S. D.; Sierra, C.; Godo, L.; Jennings, N. R.
Negotiating using rewards. Journal Article
In: Artificial Intelligence Journal., vol. 171, no. 10-15, pp. 805–837, 2007.
Abstract | Links | BibTeX | Tags: Bargaining, Bilateral Negotiation., Negotiation Tactics, Persuasive Negotiation, Repeated Negotiations
@article{eps264225,
title = {Negotiating using rewards.},
author = {S. D. Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/264225/},
year = {2007},
date = {2007-01-01},
journal = {Artificial Intelligence Journal.},
volume = {171},
number = {10-15},
pages = {805–837},
abstract = {Negotiation is a fundamental interaction mechanism in multi-agent systems because it allows self-interested agents to come to mutually beneficial agreements and partition resources efficiently and effectively. Now, in many situations, the agents need to negotiate with one another many times and so developing strategies that are effective over repeated interactions is an important challenge. Against this background, a growing body of work has examined the use of Persuasive Negotiation (PN), which involves negotiating using rhetorical arguments (such as threats, rewards, or appeals), in trying to convince an opponent to accept a given offer. Such mechanisms are especially suited to repeated encounters because they allow agents to influence the outcomes of future negotiations, while negotiating a deal in the present one, with the aim of producing results that are beneficial to both parties. To this end, in this paper, we develop a comprehensive PN mechanism for repeated interactions that makes use of rewards that can be asked for or given to. Our mechanism consists of two parts. First, a novel protocol that structures the interaction by capturing the commitments that agents incur when using rewards. Second, a new reward generation algorithm that constructs promises of rewards in future interactions as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. We then go on to develop a specific negotiation tactic, based on this reward generation algorithm, and show that it can achieve significantly better outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation in a Multi-Move Prisoners? dilemma setting, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this.},
keywords = {Bargaining, Bilateral Negotiation., Negotiation Tactics, Persuasive Negotiation, Repeated Negotiations},
pubstate = {published},
tppubtype = {article}
}
Negotiation is a fundamental interaction mechanism in multi-agent systems because it allows self-interested agents to come to mutually beneficial agreements and partition resources efficiently and effectively. Now, in many situations, the agents need to negotiate with one another many times and so developing strategies that are effective over repeated interactions is an important challenge. Against this background, a growing body of work has examined the use of Persuasive Negotiation (PN), which involves negotiating using rhetorical arguments (such as threats, rewards, or appeals), in trying to convince an opponent to accept a given offer. Such mechanisms are especially suited to repeated encounters because they allow agents to influence the outcomes of future negotiations, while negotiating a deal in the present one, with the aim of producing results that are beneficial to both parties. To this end, in this paper, we develop a comprehensive PN mechanism for repeated interactions that makes use of rewards that can be asked for or given to. Our mechanism consists of two parts. First, a novel protocol that structures the interaction by capturing the commitments that agents incur when using rewards. Second, a new reward generation algorithm that constructs promises of rewards in future interactions as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. We then go on to develop a specific negotiation tactic, based on this reward generation algorithm, and show that it can achieve significantly better outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation in a Multi-Move Prisoners? dilemma setting, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this.
Rogers, Alex; Dash, Rajdeep K.; Ramchurn, Sarvapali D.; Vytelingum, Perukrishnen; Jennings, N. R.
Coordinating Team Players within a Noisy Iterated Prisoner?s Dilemma Tournament Journal Article
In: Theoretical Computer Science, vol. 377, no. 1-3, pp. 243–259, 2007.
Abstract | Links | BibTeX | Tags:
@article{eps263238,
title = {Coordinating Team Players within a Noisy Iterated Prisoner?s Dilemma Tournament},
author = {Alex Rogers and Rajdeep K. Dash and Sarvapali D. Ramchurn and Perukrishnen Vytelingum and N. R. Jennings},
url = {http://eprints.soton.ac.uk/263238/},
year = {2007},
date = {2007-01-01},
journal = {Theoretical Computer Science},
volume = {377},
number = {1-3},
pages = {243–259},
abstract = {In this paper, we present our investigation into the use of a team of players within a noisy Iterated Prisoner?s Dilemma (IPD) tournament. We show that the members of such a team are able to use a pre-arranged sequence of moves that they make at the start of each interaction in order to recognise one another, and that by coordinating their actions they can increase the chances that one of the team members wins the round-robin style tournament. We consider, in detail, the factors that influence the performance of this team and we show that the problem that the team members face, when they attempt to recognise one another within the noisy IPD tournament, is exactly analogous to the problem, studied in information theory, of communicating reliably over a noisy channel. Thus we demonstrate that we can use error correcting codes to implement this recognition, and by doing so, further optimise the performance of the team.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In this paper, we present our investigation into the use of a team of players within a noisy Iterated Prisoner?s Dilemma (IPD) tournament. We show that the members of such a team are able to use a pre-arranged sequence of moves that they make at the start of each interaction in order to recognise one another, and that by coordinating their actions they can increase the chances that one of the team members wins the round-robin style tournament. We consider, in detail, the factors that influence the performance of this team and we show that the problem that the team members face, when they attempt to recognise one another within the noisy IPD tournament, is exactly analogous to the problem, studied in information theory, of communicating reliably over a noisy channel. Thus we demonstrate that we can use error correcting codes to implement this recognition, and by doing so, further optimise the performance of the team.
Rogers, Alex; Dash, Rajdeep K.; Ramchurn, Sarvapali D.; Vytelingum, Perukrishnen; Jennings, N. R.
Error-Correcting Codes for Team Coordination within a Noisy Iterated Prisoner?s Dilemma Tournament Book Section
In: Kendel, Graham; Yao, Xin; Chong, Siang Yew (Ed.): The Iterated Prisoners Dilemma Competition: Celebrating the 20th Anniversary, pp. 205–229, World Scientific, 2007.
@incollection{eps263264,
title = {Error-Correcting Codes for Team Coordination within a Noisy Iterated Prisoner?s Dilemma Tournament},
author = {Alex Rogers and Rajdeep K. Dash and Sarvapali D. Ramchurn and Perukrishnen Vytelingum and N. R. Jennings},
editor = {Graham Kendel and Xin Yao and Siang Yew Chong},
url = {http://eprints.soton.ac.uk/263264/},
year = {2007},
date = {2007-01-01},
booktitle = {The Iterated Prisoners Dilemma Competition: Celebrating the 20th Anniversary},
pages = {205–229},
publisher = {World Scientific},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
2006
Karunatillake, N. C.; Jennings, N. R.; Rahwan, I.; Ramchurn, S. D.
Managing Social Influences through Argumentation-Based Negotiation Proceedings Article
In: Third International Workshop on Argumentation in Multi-Agent Systems (ArgMAS 2006), pp. 35–52, 2006, (Event Dates: 8th May 2006).
Abstract | Links | BibTeX | Tags:
@inproceedings{eps262022,
title = {Managing Social Influences through Argumentation-Based Negotiation},
author = {N. C. Karunatillake and N. R. Jennings and I. Rahwan and S. D. Ramchurn},
url = {http://eprints.soton.ac.uk/262022/},
year = {2006},
date = {2006-01-01},
booktitle = {Third International Workshop on Argumentation in Multi-Agent Systems (ArgMAS 2006)},
pages = {35–52},
abstract = {Social influences play an important part in the actions that an individual agent may perform within a multi-agent society. However, the incomplete knowledge and the diverse and conflicting influences present within such societies, may stop an agent from abiding by all its social influences. This may, in turn, lead to conflicts that the agents need to identify, manage, and resolve in order for the society to behave in a coherent manner. To this end, we present an empirical study of an argumentation-based negotiation (ABN) approach that allows the agents to detect such conflicts, and then manage and resolve them through the use of argumentative dialogues. To test our theory, we map our ABN model to a multi-agent task allocation scenario. Our results show that using an argumentation approach allows agents to both efficiently and effectively manage their social influences even under high degrees of incompleteness. Finally, we show that allowing agents to argue and resolve such conflicts early in the negotiation encounter increases their efficiency in managing social influences.},
note = {Event Dates: 8th May 2006},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Social influences play an important part in the actions that an individual agent may perform within a multi-agent society. However, the incomplete knowledge and the diverse and conflicting influences present within such societies, may stop an agent from abiding by all its social influences. This may, in turn, lead to conflicts that the agents need to identify, manage, and resolve in order for the society to behave in a coherent manner. To this end, we present an empirical study of an argumentation-based negotiation (ABN) approach that allows the agents to detect such conflicts, and then manage and resolve them through the use of argumentative dialogues. To test our theory, we map our ABN model to a multi-agent task allocation scenario. Our results show that using an argumentation approach allows agents to both efficiently and effectively manage their social influences even under high degrees of incompleteness. Finally, we show that allowing agents to argue and resolve such conflicts early in the negotiation encounter increases their efficiency in managing social influences.
Ramchurn, S. D.; Sierra, C.; Godo, L.; Jennings, N. R.
Negotiating using rewards Proceedings Article
In: 5th Int. Conf. on Autonomous Agents and Multi-Agent Systems, pp. 400–407, 2006.
Abstract | Links | BibTeX | Tags: Argumentation, Bargaining, Persuasive Negotiation
@inproceedings{eps262591,
title = {Negotiating using rewards},
author = {S. D. Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/262591/},
year = {2006},
date = {2006-01-01},
booktitle = {5th Int. Conf. on Autonomous Agents and Multi-Agent Systems},
journal = {Proc. 5th Int. Conf. on Autonomous Agents and Multi-Agent Systems, Hakodate, Japan},
pages = {400–407},
abstract = {In situations where self-interested agents interact repeatedly, it is important that they are endowed with negotiation techniques that enable them to reach agreements that are profitable in the long run. To this end, we devise a novel negotiation algorithm that generates promises of rewards in future interactions, as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. Moreover, we thus develop a specific negotiation tactic based on this reward generation algorithm and show that it can achieve significantly bettter outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this under concrete settings.},
keywords = {Argumentation, Bargaining, Persuasive Negotiation},
pubstate = {published},
tppubtype = {inproceedings}
}
In situations where self-interested agents interact repeatedly, it is important that they are endowed with negotiation techniques that enable them to reach agreements that are profitable in the long run. To this end, we devise a novel negotiation algorithm that generates promises of rewards in future interactions, as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. Moreover, we thus develop a specific negotiation tactic based on this reward generation algorithm and show that it can achieve significantly bettter outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this under concrete settings.
2005
Ashri, R.; Ramchurn, S. D.; Sabater, J.; Luck, M.; Jennings, N. R.
Trust evaluation through relationship analysis Proceedings Article
In: 4th Int Joint Conf. on Autonomous Agents and Multi-Agent Systems, pp. 1005–1011, 2005.
Abstract | Links | BibTeX | Tags: Multi-Agent Systems., Relationships, Reputation, Trust
@inproceedings{eps260806,
title = {Trust evaluation through relationship analysis},
author = {R. Ashri and S. D. Ramchurn and J. Sabater and M. Luck and N. R. Jennings},
url = {http://eprints.soton.ac.uk/260806/},
year = {2005},
date = {2005-01-01},
booktitle = {4th Int Joint Conf. on Autonomous Agents and Multi-Agent Systems},
journal = {Proceedings: 4th International Joint Conference on Autonomous Agents and Multi-Agent Systems},
pages = {1005–1011},
abstract = {Current mechanisms for evaluating the trustworthiness of an agent within an electronic marketplace depend either on using a history of interactions or on recommendations from other agents. In the first case, these requirements limit what an agent with no prior interaction history can do. In the second case, they transform the problem into one of trusting the recommending agent. However, these mechanisms do not consider the relationships between agents that arise through interactions (such as buying or selling) or through overarching organisational structures (such as hierarchical or flat), which can also aid in evaluating trustworthiness. In response, this paper outlines a method that enables agents to evaluate the trustworthiness of their counterparts, based solely on an analysis of such relationships. Specifically, relationships are identified using a generic technique in conjunction with a basic model for agentbased marketplaces. They are then interpreted through a trust model that enables the inference of trust valuations based on the different types of relationships. In this way, we provide a further component for a trust evaluation model that addresses some of the limitations of existing work.},
keywords = {Multi-Agent Systems., Relationships, Reputation, Trust},
pubstate = {published},
tppubtype = {inproceedings}
}
Current mechanisms for evaluating the trustworthiness of an agent within an electronic marketplace depend either on using a history of interactions or on recommendations from other agents. In the first case, these requirements limit what an agent with no prior interaction history can do. In the second case, they transform the problem into one of trusting the recommending agent. However, these mechanisms do not consider the relationships between agents that arise through interactions (such as buying or selling) or through overarching organisational structures (such as hierarchical or flat), which can also aid in evaluating trustworthiness. In response, this paper outlines a method that enables agents to evaluate the trustworthiness of their counterparts, based solely on an analysis of such relationships. Specifically, relationships are identified using a generic technique in conjunction with a basic model for agentbased marketplaces. They are then interpreted through a trust model that enables the inference of trust valuations based on the different types of relationships. In this way, we provide a further component for a trust evaluation model that addresses some of the limitations of existing work.
Blankenburg, B.; Dash, R. K.; Ramchurn, S. D.; Klusch, M.; Jennings, N. R.
Trusted kernel-based coalition formation Proceedings Article
In: Proc. 4th Int Joint Conf on Autonomous Agents and Multi-Agent Systems, pp. 989–996, 2005.
Abstract | Links | BibTeX | Tags:
@inproceedings{eps260808,
title = {Trusted kernel-based coalition formation},
author = {B. Blankenburg and R. K. Dash and S. D. Ramchurn and M. Klusch and N. R. Jennings},
url = {http://eprints.soton.ac.uk/260808/},
year = {2005},
date = {2005-01-01},
booktitle = {Proc. 4th Int Joint Conf on Autonomous Agents and Multi-Agent Systems},
journal = {Proceedings: 4th International Joint Conference on Autonomous Agents and Multi-agent Systems},
pages = {989–996},
abstract = {We define Trusted Kernel-based Coalition Formation as a novel extension to the traditional kernel-based coalition formation process which ensures agents choose the most reliable coalition partners and are guaranteed to obtain the payment they deserve. To this end, we develop an encryption-based communication protocol and a payment scheme which ensure that agents cannot manipulate the mechanism to their own benefit. Moreover, we integrate a generic trust model in the coalition formation process that permits the selection of the most reliable agents over repeated coalition games. We empirically evaluate our mechanism when iterated and show that, in the long run, it always chooses the coalition structure that has the maximum expected value and determines the payoffs that match their level of reliability.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We define Trusted Kernel-based Coalition Formation as a novel extension to the traditional kernel-based coalition formation process which ensures agents choose the most reliable coalition partners and are guaranteed to obtain the payment they deserve. To this end, we develop an encryption-based communication protocol and a payment scheme which ensure that agents cannot manipulate the mechanism to their own benefit. Moreover, we integrate a generic trust model in the coalition formation process that permits the selection of the most reliable agents over repeated coalition games. We empirically evaluate our mechanism when iterated and show that, in the long run, it always chooses the coalition structure that has the maximum expected value and determines the payoffs that match their level of reliability.
Ramchurn, S. D.; Jennings, N. R.
Trust in agent-based software Book Section
In: Mansell, R.; Collins, B. S. (Ed.): Trust and Crime in Information Societies, pp. 165–204, Elgar Publishing, 2005.
@incollection{eps260823,
title = {Trust in agent-based software},
author = {S. D. Ramchurn and N. R. Jennings},
editor = {R. Mansell and B. S. Collins},
url = {http://eprints.soton.ac.uk/260823/},
year = {2005},
date = {2005-01-01},
booktitle = {Trust and Crime in Information Societies},
pages = {165–204},
publisher = {Elgar Publishing},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
2004
Dash, R. K.; Ramchurn, S. D.; Jennings, N. R.
Trust-Based Mechanism Design Proceedings Article
In: 3rd Int. Conf. on Autonomous Agents and Multi-Agent Systems, pp. 748–755, 2004, (Event Dates: 19-23 July 2004).
Abstract | Links | BibTeX | Tags:
@inproceedings{eps259352,
title = {Trust-Based Mechanism Design},
author = {R. K. Dash and S. D. Ramchurn and N. R. Jennings},
url = {http://eprints.soton.ac.uk/259352/},
year = {2004},
date = {2004-01-01},
booktitle = {3rd Int. Conf. on Autonomous Agents and Multi-Agent Systems},
pages = {748–755},
abstract = {We define trust-based mechanism design as an augmentation of traditional mechanism design in which agents take into account the degree of trust that they have in their counterparts when determining their allocations. To this end, we develop an efficient, individually rational, and incentive compatible mechanism based on trust. This mechanism is embedded in a task allocation scenario in which the trust in an agent is derived from the reported performance success of that agent by all the other agents in the system. We also empirically study the evolution of our mechanism when iterated and show that, in the long run, it always chooses the most successful and cheapest agents to fulfill an allocation and chooses better allocations than other comparable models when faced with biased reporting.},
note = {Event Dates: 19-23 July 2004},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We define trust-based mechanism design as an augmentation of traditional mechanism design in which agents take into account the degree of trust that they have in their counterparts when determining their allocations. To this end, we develop an efficient, individually rational, and incentive compatible mechanism based on trust. This mechanism is embedded in a task allocation scenario in which the trust in an agent is derived from the reported performance success of that agent by all the other agents in the system. We also empirically study the evolution of our mechanism when iterated and show that, in the long run, it always chooses the most successful and cheapest agents to fulfill an allocation and chooses better allocations than other comparable models when faced with biased reporting.
Ramchurn, S. D.; Deitch, B.; Thompson, M. K.; Roure, D. C.; Jennings, N. R.; Luck, M.
Minimising intrusiveness in pervasive computing environments using multi-agent negotiation Proceedings Article
In: First Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous'04), pp. 364–372, IEEE, 2004, (Event Dates: August 22 - 26, 2004).
Abstract | Links | BibTeX | Tags:
@inproceedings{eps259566,
title = {Minimising intrusiveness in pervasive computing environments using multi-agent negotiation},
author = {S. D. Ramchurn and B. Deitch and M. K. Thompson and D. C. Roure and N. R. Jennings and M. Luck},
url = {http://eprints.soton.ac.uk/259566/},
year = {2004},
date = {2004-01-01},
booktitle = {First Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous'04)},
pages = {364–372},
publisher = {IEEE},
abstract = {This paper highlights intrusiveness as a key issue in the field of pervasive computing environments and presents a multi-agent approach to tackling it. Specifically, we discuss how interruptions can impact on individual and group tasks and how they can be managed by taking into account user and group preferences through negotiation between software agents. The system we develop is implemented on the Jabber platform and is deployed in the context of a meeting room scenario.},
note = {Event Dates: August 22 - 26, 2004},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper highlights intrusiveness as a key issue in the field of pervasive computing environments and presents a multi-agent approach to tackling it. Specifically, we discuss how interruptions can impact on individual and group tasks and how they can be managed by taking into account user and group preferences through negotiation between software agents. The system we develop is implemented on the Jabber platform and is deployed in the context of a meeting room scenario.
Ramchurn, S. D.; Huynh, T. D.; Jennings, N. R.
Trust in Multiagent Systems Journal Article
In: The Knowledge Engineering Review, vol. 19, no. 1, pp. 1–25, 2004.
Abstract | Links | BibTeX | Tags:
@article{eps259564,
title = {Trust in Multiagent Systems},
author = {S. D. Ramchurn and T. D. Huynh and N. R. Jennings},
url = {http://eprints.soton.ac.uk/259564/},
year = {2004},
date = {2004-01-01},
journal = {The Knowledge Engineering Review},
volume = {19},
number = {1},
pages = {1–25},
abstract = {Trust is a fundamental concern in large-scale open distributed systems. It lies at the core of all interactions between the entities that have to operate in such uncertain and constantly changing environments. Given this complexity, these components, and the ensuing system, are increasingly being conceptualised, designed, and built using agent-based techniques and, to this end, this paper examines the specific role of trust in multi-agent systems. In particular, we survey the state of the art and provide an account of the main directions along which research efforts are being focused. In so doing, we critically evaluate the relative strengths and weaknesses of the main models that have been proposed and show how, fundamentally, they all seek to minimise the uncertainty in interactions. Finally, we outline the areas that require further research in order to develop a comprehensive treatment of trust in complex computational settings.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Trust is a fundamental concern in large-scale open distributed systems. It lies at the core of all interactions between the entities that have to operate in such uncertain and constantly changing environments. Given this complexity, these components, and the ensuing system, are increasingly being conceptualised, designed, and built using agent-based techniques and, to this end, this paper examines the specific role of trust in multi-agent systems. In particular, we survey the state of the art and provide an account of the main directions along which research efforts are being focused. In so doing, we critically evaluate the relative strengths and weaknesses of the main models that have been proposed and show how, fundamentally, they all seek to minimise the uncertainty in interactions. Finally, we outline the areas that require further research in order to develop a comprehensive treatment of trust in complex computational settings.
Ramchurn, Sarvapali
Multi-Agent Negotiation using Trust and Persuasion PhD Thesis
University of Southampton, 2004.
Abstract | Links | BibTeX | Tags: Argumentation-based Negotiation, multi-agent systems, Negotiation, Persuasion, Trust
@phdthesis{eps260200,
title = {Multi-Agent Negotiation using Trust and Persuasion},
author = {Sarvapali Ramchurn},
url = {http://eprints.soton.ac.uk/260200/},
year = {2004},
date = {2004-01-01},
school = {University of Southampton},
abstract = {In this thesis, we propose a panoply of tools and techniques to manage inter-agent dependencies in open, distributed multi-agent systems that have significant degrees of uncertainty. In particular, we focus on situations in which agents are involved in repeated interactions where they need to negotiate to resolve conflicts that may arise between them. To this end, we endow agents with decision making models that exploit the notion of trust and use persuasive techniques during the negotiation process to reduce the level of uncertainty and achieve better deals in the long run. Firstly, we develop and evaluate a new trust model (called CREDIT) that allows agents to measure the degree of trust they should place in their opponents. This model reduces the uncertainty that agents have about their opponents' reliability. Thus, over repeated interactions, CREDIT enables agents to model their opponents' reliability using probabilistic techniques and a fuzzy reasoning mechanism that allows the combination of measures based on reputation (indirect interactions) and confidence (direct interactions). In so doing, CREDIT takes a wider range of behaviour-influencing factors into account than existing models, including the norms of the agents and the institution within which transactions occur. We then explore a novel application of trust models by showing how the measures developed in CREDIT ca be applied negotiations in multiple encounters. Specifically we show that agents that use CREDIT are able to avoid unreliable agents, both during the selection of interaction partners and during the negotiation process itself by using trust to adjust their negotiation stance. Also, we empirically show that agents are able to reach good deals with agents that are unreliable to some degree (rather than completely unreliable) and with those that try to strategically exploit their opponent. Secondly, having applied CREDIT to negotiations, we further extend the application of trust to reduce uncertainty about the reliability of agents in mechanism design (where the honesty of agents is elicited by the protocol). Thus, we develop $backslash$acftbmd that allows agents using a trust model (such as CREDIT) to reach efficient agreements that choose the most reliable agents in the long run. In particular, we show that our mechanism enforces truth-telling from the agents (i.e. it is incentive compatible), both about their perceived reliability of their opponent and their valuations for the goods to be traded. In proving the latter properties, our trust-based mechanism is shown to be the first reputation mechanism that implements individual rationality, incentive compatibility, and efficiency. Our trust-based mechanism is also empirically evaluated and shown to be better than other comparable models in reaching the outcome that maximises all the negotiating agents' utilities and in choosing the most reliable agents in the long run. Thirdly, having explored ways to reduce uncertainties about reliability and honesty, we use persuasive negotiation techniques to tackle issues associated with uncertainties that agents have about the preferences and the space of possible agreements. To this end, we propose a novel protocol and reasoning mechanism that agents can use to generate and evaluate persuasive elements, such as promises of future rewards, to support the offers they make during negotiation. These persuasive elements aim to make offers more attractive over multiple encounters given the absence of information about an opponent's discount factors or exact payoffs. Specifically, we empirically demonstrate that agents are able to achieve a larger number of agreements and a higher expected utility over repeated encounters when they are given the capability to give or ask for rewards. Moreover, we develop a novel strategy using this protocol and show that it outperforms existing state of the art heuristic negotiation models. Finally, the applicability of persuasive negotiation and CREDIT is exemplified through a practical implementation in a pervasive computing environment. In this context, the negotiation mechanism is implemented in an instant messaging platform (JABBER) and used to resolve conflicts between group and individual preferences that arise in a meeting room scenario. In particular, we show how persuasive negotiation and trust permit a flexible management of interruptions by allowing intrusions to happen at appropriate times during the meeting while still managing to satisfy the preferences of all parties present.},
keywords = {Argumentation-based Negotiation, multi-agent systems, Negotiation, Persuasion, Trust},
pubstate = {published},
tppubtype = {phdthesis}
}
In this thesis, we propose a panoply of tools and techniques to manage inter-agent dependencies in open, distributed multi-agent systems that have significant degrees of uncertainty. In particular, we focus on situations in which agents are involved in repeated interactions where they need to negotiate to resolve conflicts that may arise between them. To this end, we endow agents with decision making models that exploit the notion of trust and use persuasive techniques during the negotiation process to reduce the level of uncertainty and achieve better deals in the long run. Firstly, we develop and evaluate a new trust model (called CREDIT) that allows agents to measure the degree of trust they should place in their opponents. This model reduces the uncertainty that agents have about their opponents' reliability. Thus, over repeated interactions, CREDIT enables agents to model their opponents' reliability using probabilistic techniques and a fuzzy reasoning mechanism that allows the combination of measures based on reputation (indirect interactions) and confidence (direct interactions). In so doing, CREDIT takes a wider range of behaviour-influencing factors into account than existing models, including the norms of the agents and the institution within which transactions occur. We then explore a novel application of trust models by showing how the measures developed in CREDIT ca be applied negotiations in multiple encounters. Specifically we show that agents that use CREDIT are able to avoid unreliable agents, both during the selection of interaction partners and during the negotiation process itself by using trust to adjust their negotiation stance. Also, we empirically show that agents are able to reach good deals with agents that are unreliable to some degree (rather than completely unreliable) and with those that try to strategically exploit their opponent. Secondly, having applied CREDIT to negotiations, we further extend the application of trust to reduce uncertainty about the reliability of agents in mechanism design (where the honesty of agents is elicited by the protocol). Thus, we develop $backslash$acftbmd that allows agents using a trust model (such as CREDIT) to reach efficient agreements that choose the most reliable agents in the long run. In particular, we show that our mechanism enforces truth-telling from the agents (i.e. it is incentive compatible), both about their perceived reliability of their opponent and their valuations for the goods to be traded. In proving the latter properties, our trust-based mechanism is shown to be the first reputation mechanism that implements individual rationality, incentive compatibility, and efficiency. Our trust-based mechanism is also empirically evaluated and shown to be better than other comparable models in reaching the outcome that maximises all the negotiating agents' utilities and in choosing the most reliable agents in the long run. Thirdly, having explored ways to reduce uncertainties about reliability and honesty, we use persuasive negotiation techniques to tackle issues associated with uncertainties that agents have about the preferences and the space of possible agreements. To this end, we propose a novel protocol and reasoning mechanism that agents can use to generate and evaluate persuasive elements, such as promises of future rewards, to support the offers they make during negotiation. These persuasive elements aim to make offers more attractive over multiple encounters given the absence of information about an opponent's discount factors or exact payoffs. Specifically, we empirically demonstrate that agents are able to achieve a larger number of agreements and a higher expected utility over repeated encounters when they are given the capability to give or ask for rewards. Moreover, we develop a novel strategy using this protocol and show that it outperforms existing state of the art heuristic negotiation models. Finally, the applicability of persuasive negotiation and CREDIT is exemplified through a practical implementation in a pervasive computing environment. In this context, the negotiation mechanism is implemented in an instant messaging platform (JABBER) and used to resolve conflicts between group and individual preferences that arise in a meeting room scenario. In particular, we show how persuasive negotiation and trust permit a flexible management of interruptions by allowing intrusions to happen at appropriate times during the meeting while still managing to satisfy the preferences of all parties present.
Ramchurn, Sarvapali; Sierra, C.; Godo, L.; Jennings, N. R.
Devising a trust model for multi-agent interactions using confidence and reputation Journal Article
In: International Journal of Applied Artificial Intelligence, vol. 18, no. 9-10, pp. 833–852, 2004.
@article{eps260155,
title = {Devising a trust model for multi-agent interactions using confidence and reputation},
author = {Sarvapali Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/260155/},
year = {2004},
date = {2004-01-01},
journal = {International Journal of Applied Artificial Intelligence},
volume = {18},
number = {9-10},
pages = {833–852},
keywords = {},
pubstate = {published},
tppubtype = {article}
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2003
Rahwan, I.; Ramchurn, Sarvapali; Jennings, N. R.; McBurney, P.; Parsons, S.; Sonenberg, L.
Argumentation-based negotiation Journal Article
In: The Knowledge Engineering Review, vol. 18, no. 4, pp. 343–375, 2003.
Abstract | Links | BibTeX | Tags:
@article{eps258850,
title = {Argumentation-based negotiation},
author = {I. Rahwan and Sarvapali Ramchurn and N. R. Jennings and P. McBurney and S. Parsons and L. Sonenberg},
url = {http://eprints.soton.ac.uk/258850/},
year = {2003},
date = {2003-01-01},
journal = {The Knowledge Engineering Review},
volume = {18},
number = {4},
pages = {343–375},
abstract = {Negotiation is essential in settings where autonomous agents have con- flicting interests and a desire to cooperate. For this reason, mechanisms in which agents exchange potential agreements according to various rules of interaction have become very popular in recent years as evident, for example, in the auction and mechanism design community. However, a growing body of research is now emerging which points out limitations in such mechanisms and advocates the idea that agents can increase the likelihood and quality of an agreement by exchanging arguments which in- fluence each others? states. This community further argues that argument exchange is sometimes essential when various assumptions about agent rationality cannot be satisfied. To this end, in this article, we identify the main research motivations and ambitions behind work in the field. We then provide a conceptual framework through which we outline the core elements and features required by agents engaged in argumentation-based negotiation, as well as the environment that hosts these agents. For each of these elements, we survey and evaluate existing proposed techniques in the literature and highlight the major challenges that need to be addressed if argument-based negotiation research is to reach its full potential.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Negotiation is essential in settings where autonomous agents have con- flicting interests and a desire to cooperate. For this reason, mechanisms in which agents exchange potential agreements according to various rules of interaction have become very popular in recent years as evident, for example, in the auction and mechanism design community. However, a growing body of research is now emerging which points out limitations in such mechanisms and advocates the idea that agents can increase the likelihood and quality of an agreement by exchanging arguments which in- fluence each others? states. This community further argues that argument exchange is sometimes essential when various assumptions about agent rationality cannot be satisfied. To this end, in this article, we identify the main research motivations and ambitions behind work in the field. We then provide a conceptual framework through which we outline the core elements and features required by agents engaged in argumentation-based negotiation, as well as the environment that hosts these agents. For each of these elements, we survey and evaluate existing proposed techniques in the literature and highlight the major challenges that need to be addressed if argument-based negotiation research is to reach its full potential.
Ramchurn, S. D.; Jennings, N. R.; Sierra, C.
Persuasive negotiation for autonomous agents: A rhetorical approach Proceedings Article
In: IJCAI Workshop on Computational Models of Natural Argument, pp. 9–17, 2003.
Abstract | Links | BibTeX | Tags:
@inproceedings{eps258541,
title = {Persuasive negotiation for autonomous agents: A rhetorical approach},
author = {S. D. Ramchurn and N. R. Jennings and C. Sierra},
url = {http://eprints.soton.ac.uk/258541/},
year = {2003},
date = {2003-01-01},
booktitle = {IJCAI Workshop on Computational Models of Natural Argument},
pages = {9–17},
abstract = {Persuasive negotiation occurs when autonomous agents exchange proposals that are backed up by rhetorical arguments (such as threats, rewards, or appeals). The role of such rhetorical arguments is to persuade the negotiation opponent to accept proposals more readily. To this end, this paper presents a rhetorical model of persuasion that defines the main types of rhetorical particles that are used and that provides a decision making model to enable an agent to determine what type of rhetorical argument to send in a given context and how to evaluate rhetorical arguments that are received. The model is empirically evaluated and we show that it is effective and efficient in reaching agreements.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Persuasive negotiation occurs when autonomous agents exchange proposals that are backed up by rhetorical arguments (such as threats, rewards, or appeals). The role of such rhetorical arguments is to persuade the negotiation opponent to accept proposals more readily. To this end, this paper presents a rhetorical model of persuasion that defines the main types of rhetorical particles that are used and that provides a decision making model to enable an agent to determine what type of rhetorical argument to send in a given context and how to evaluate rhetorical arguments that are received. The model is empirically evaluated and we show that it is effective and efficient in reaching agreements.
Ramchurn, Sarvapali; Sierra, C.; Godo, L.; Jennings, N. R.
A computational trust model for multi-agent interactions based on confidence and reputation Proceedings Article
In: 6th International Workshop of Deception, Fraud and Trust in Agent Societies, pp. 69–75, 2003, (Event Dates: 2003).
Abstract | Links | BibTeX | Tags:
@inproceedings{eps258542,
title = {A computational trust model for multi-agent interactions based on confidence and reputation},
author = {Sarvapali Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/258542/},
year = {2003},
date = {2003-01-01},
booktitle = {6th International Workshop of Deception, Fraud and Trust in Agent Societies},
pages = {69–75},
abstract = {In open environments in which autonomous agents can break contracts, computational models of trust have an important role to play in determining who to interact with and how interactions unfold. To this end, we develop such a trust model, based on confi- dence and reputation, and show how it can be concretely applied, using fuzzy sets, to guide agents in evaluating past interactions and in establishing new contracts with one another.},
note = {Event Dates: 2003},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In open environments in which autonomous agents can break contracts, computational models of trust have an important role to play in determining who to interact with and how interactions unfold. To this end, we develop such a trust model, based on confi- dence and reputation, and show how it can be concretely applied, using fuzzy sets, to guide agents in evaluating past interactions and in establishing new contracts with one another.
2002
Panzarasa, P.; Ramchurn, S. D.; Jennings, Nick
Intrusiveness, Trust and Argumentation: Using Automated Negotiation to Inhibit the Transmission of Disruptive Information Proceedings Article
In: Proceedings of the International Conference on Computational Social and Organizational Systems, 2002.
Abstract | Links | BibTeX | Tags:
@inproceedings{eps272014,
title = {Intrusiveness, Trust and Argumentation: Using Automated Negotiation to Inhibit the Transmission of Disruptive Information},
author = {P. Panzarasa and S. D. Ramchurn and Nick Jennings},
url = {http://eprints.soton.ac.uk/272014/},
year = {2002},
date = {2002-01-01},
booktitle = {Proceedings of the International Conference on Computational Social and Organizational Systems},
abstract = {The question of how to promote the growth and diffusion of information has been extensively addressed by a wide research community. A common assumption underpinning most studies is that the information to be transmitted is useful and of high quality. In this paper, we endorse a complementary perspective. We investigate how the growth and diffusion of high quality information can be managed and maximized by preventing, dampening and minimizing the diffusion of low quality, unwanted information. To this end, we focus on the conflict between pervasive computing environments and the joint activities undertaken in parallel local social contexts. When technologies for distributed activities (e.g. mobile technology) develop, both artifacts and services that enable people to participate in non-local contexts are likely to intrude on local situations. As a mechanism for minimizing the intrusion of the technology, we develop a computational model of argumentation-based negotiation among autonomous agents. A key component in the model is played by trust: what arguments are used and how they are evaluated depend on how trustworthy the agents judge one another. To gain an insight into the implications of the model, we conduct a number of virtual experiments. Results enable us to explore how intrusiveness is affected by trust, the negotiation network and the agents' abilities of conducting argumentation.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The question of how to promote the growth and diffusion of information has been extensively addressed by a wide research community. A common assumption underpinning most studies is that the information to be transmitted is useful and of high quality. In this paper, we endorse a complementary perspective. We investigate how the growth and diffusion of high quality information can be managed and maximized by preventing, dampening and minimizing the diffusion of low quality, unwanted information. To this end, we focus on the conflict between pervasive computing environments and the joint activities undertaken in parallel local social contexts. When technologies for distributed activities (e.g. mobile technology) develop, both artifacts and services that enable people to participate in non-local contexts are likely to intrude on local situations. As a mechanism for minimizing the intrusion of the technology, we develop a computational model of argumentation-based negotiation among autonomous agents. A key component in the model is played by trust: what arguments are used and how they are evaluated depend on how trustworthy the agents judge one another. To gain an insight into the implications of the model, we conduct a number of virtual experiments. Results enable us to explore how intrusiveness is affected by trust, the negotiation network and the agents' abilities of conducting argumentation.
61.
Rigas, Emmanouil; Gerding, Enrico; Stein, Sebastian; Ramchurn, Sarvapali D; Bassiliades, Nick
Mechanism Design for Efficient Online and Offline Allocation of Electric Vehicles to Charging Stations Journal Article
In: CoRR, vol. abs/2007.09715, 2020.
@article{DBLP:journals/corr/abs-2007-09715,
title = {Mechanism Design for Efficient Online and Offline Allocation of Electric
Vehicles to Charging Stations},
author = {Emmanouil Rigas and Enrico Gerding and Sebastian Stein and Sarvapali D Ramchurn and Nick Bassiliades},
url = {https://arxiv.org/abs/2007.09715},
year = {2020},
date = {2020-01-01},
journal = {CoRR},
volume = {abs/2007.09715},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
62.
Abeywickrama, Dhaminda B; Cirstea, Corina; Ramchurn, Sarvapali D
Model Checking Human-Agent Collectives for Responsible AI Proceedings Article
In: 2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), pp. 1–8, IEEE 2019.
@inproceedings{abeywickrama2019model,
title = {Model Checking Human-Agent Collectives for Responsible AI},
author = {Dhaminda B Abeywickrama and Corina Cirstea and Sarvapali D Ramchurn},
year = {2019},
date = {2019-01-01},
booktitle = {2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)},
pages = {1–8},
organization = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
63.
Beal, Ryan; Norman, Timothy J; Ramchurn, Sarvapali D
Artificial intelligence for team sports: a survey Journal Article
In: The Knowledge Engineering Review, vol. 34, 2019.
@article{beal2019artificial,
title = {Artificial intelligence for team sports: a survey},
author = {Ryan Beal and Timothy J Norman and Sarvapali D Ramchurn},
year = {2019},
date = {2019-01-01},
journal = {The Knowledge Engineering Review},
volume = {34},
publisher = {Cambridge University Press},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
64.
Abioye, Ayodeji Opeyemi; Prior, Stephen D; Thomas, Glyn T; Saddington, Peter; Ramchurn, Sarvapali D
Multimodal human aerobotic interaction Book Section
In: Unmanned Aerial Vehicles: Breakthroughs in Research and Practice, pp. 142–165, IGI Global, 2019.
@incollection{abioye2019multimodal,
title = {Multimodal human aerobotic interaction},
author = {Ayodeji Opeyemi Abioye and Stephen D Prior and Glyn T Thomas and Peter Saddington and Sarvapali D Ramchurn},
year = {2019},
date = {2019-01-01},
booktitle = {Unmanned Aerial Vehicles: Breakthroughs in Research and Practice},
pages = {142–165},
publisher = {IGI Global},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
65.
Fuentes, Carolina; Porcheron, Martin; Fischer, Joel E; Costanza, Enrico; Malilk, Obaid; Ramchurn, Sarvapali D
Tracking the Consumption of Home Essentials Proceedings Article
In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 639, ACM 2019.
@inproceedings{fuentes2019tracking,
title = {Tracking the Consumption of Home Essentials},
author = {Carolina Fuentes and Martin Porcheron and Joel E Fischer and Enrico Costanza and Obaid Malilk and Sarvapali D Ramchurn},
year = {2019},
date = {2019-01-01},
booktitle = {Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems},
pages = {639},
organization = {ACM},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
66.
Koufakis, Alexandros-Michail; Rigas, Emmanouil S; Bassiliades, Nick; Ramchurn, Sarvapali D
Offline and Online Electric Vehicle Charging Scheduling With V2V Energy Transfer Journal Article
In: IEEE Transactions on Intelligent Transportation Systems, 2019.
@article{koufakis2019offline,
title = {Offline and Online Electric Vehicle Charging Scheduling With V2V Energy Transfer},
author = {Alexandros-Michail Koufakis and Emmanouil S Rigas and Nick Bassiliades and Sarvapali D Ramchurn},
year = {2019},
date = {2019-01-01},
journal = {IEEE Transactions on Intelligent Transportation Systems},
publisher = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
67.
Seitaridis, Andreas; Rigas, Emmanouil S; Bassiliades, Nick; Ramchurn, Sarvapali D
An Agent-based Negotiation Scheme for the Distribution of Electric Vehicles Across a Set of Charging Stations Journal Article
In: Simulation Modelling Practice and Theory, pp. 102040, 2019.
@article{seitaridis2019agent,
title = {An Agent-based Negotiation Scheme for the Distribution of Electric Vehicles Across a Set of Charging Stations},
author = {Andreas Seitaridis and Emmanouil S Rigas and Nick Bassiliades and Sarvapali D Ramchurn},
year = {2019},
date = {2019-01-01},
journal = {Simulation Modelling Practice and Theory},
pages = {102040},
publisher = {Elsevier},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
68.
Abioye, Ayodeji Opeyemi; Prior, Stephen D; Saddington, Peter; Ramchurn, Sarvapali D
Effects of Varying Noise Levels and Lighting Levels on Multimodal Speech and Visual Gesture Interaction with Aerobots Journal Article
In: Applied Sciences, vol. 9, no. 10, pp. 2066, 2019.
@article{abioye2019effects,
title = {Effects of Varying Noise Levels and Lighting Levels on Multimodal Speech and Visual Gesture Interaction with Aerobots},
author = {Ayodeji Opeyemi Abioye and Stephen D Prior and Peter Saddington and Sarvapali D Ramchurn},
year = {2019},
date = {2019-01-01},
journal = {Applied Sciences},
volume = {9},
number = {10},
pages = {2066},
publisher = {Multidisciplinary Digital Publishing Institute},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
69.
Rigas, Emmanouil; Ramchurn, Sarvapali; Bassiliades, Nick
Algorithms for electric vehicle scheduling in large-scale mobility-on-demand schemes Journal Article
In: Artificial Intelligence, vol. 262, pp. 248–278, 2018.
@article{soton422097,
title = {Algorithms for electric vehicle scheduling in large-scale mobility-on-demand schemes},
author = {Emmanouil Rigas and Sarvapali Ramchurn and Nick Bassiliades},
url = {https://eprints.soton.ac.uk/422097/},
year = {2018},
date = {2018-09-01},
journal = {Artificial Intelligence},
volume = {262},
pages = {248–278},
abstract = {We study a setting where Electric Vehicles (EVs) can be hired to drive from pick-up to drop-off points in a Mobility-on-Demand (MoD) scheme. The goal of the system is, either to maximize the number of customers that are serviced, or the total EV utilization. To do so, we characterise the optimisation problem as a max-flow problem in order to determine the set of feasible trips given the available EVs at each location. We then model and solve the EV-to-trip scheduling problem offline and optimally using Mixed Integer Programming (MIP) techniques and show that the solution scales up to medium sized problems. Given this, we develop two non-optimal algorithms, namely an incremental-MIP algorithm for medium to large problems and a greedy heuristic algorithm for very large problems. Moreover, we develop a tabu search-based local search technique to further improve upon and compare against the solution of the non-optimal algorithms. We study the performance of these algorithms in settings where either battery swap or battery charge at each station is used to cope with the EVs' limited driving range. Moreover, in settings where EVs need to be scheduled online, we propose a novel algorithm that accounts for the uncertainty in future trip requests. All algorithms are empirically evaluated using real-world data of locations of shared vehicle pick-up and drop-off stations. In our experiments, we observe that when all EVs carry the same battery which is large enough for the longest trips, the greedy algorithm with battery swap with the max-flow solution as a pre-processing step, provides the optimal solution. At the same time, the greedy algorithm with battery charge is close to the optimal (97% on average) and is further improved when local search is used. When some EVs do not have a large enough battery to execute some of the longest trips, the incremental-MIP generates solutions slightly better than the greedy, while the optimal algorithm is the best but scales up to medium sized problems only. Moreover, the online algorithm is shown to be on average at least 90% of the optimal. Finally, the greedy algorithm scales to 10-times more tasks than the incremental-MIP and 1000-times more than the static MIP in reasonable time.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We study a setting where Electric Vehicles (EVs) can be hired to drive from pick-up to drop-off points in a Mobility-on-Demand (MoD) scheme. The goal of the system is, either to maximize the number of customers that are serviced, or the total EV utilization. To do so, we characterise the optimisation problem as a max-flow problem in order to determine the set of feasible trips given the available EVs at each location. We then model and solve the EV-to-trip scheduling problem offline and optimally using Mixed Integer Programming (MIP) techniques and show that the solution scales up to medium sized problems. Given this, we develop two non-optimal algorithms, namely an incremental-MIP algorithm for medium to large problems and a greedy heuristic algorithm for very large problems. Moreover, we develop a tabu search-based local search technique to further improve upon and compare against the solution of the non-optimal algorithms. We study the performance of these algorithms in settings where either battery swap or battery charge at each station is used to cope with the EVs' limited driving range. Moreover, in settings where EVs need to be scheduled online, we propose a novel algorithm that accounts for the uncertainty in future trip requests. All algorithms are empirically evaluated using real-world data of locations of shared vehicle pick-up and drop-off stations. In our experiments, we observe that when all EVs carry the same battery which is large enough for the longest trips, the greedy algorithm with battery swap with the max-flow solution as a pre-processing step, provides the optimal solution. At the same time, the greedy algorithm with battery charge is close to the optimal (97% on average) and is further improved when local search is used. When some EVs do not have a large enough battery to execute some of the longest trips, the incremental-MIP generates solutions slightly better than the greedy, while the optimal algorithm is the best but scales up to medium sized problems only. Moreover, the online algorithm is shown to be on average at least 90% of the optimal. Finally, the greedy algorithm scales to 10-times more tasks than the incremental-MIP and 1000-times more than the static MIP in reasonable time.
70.
Ayodeji, Opeyemi Abioye; Prior, Stephen; Thomas, Trevor; Saddington, Peter; Ramchurn, Sarvapali D.
The multimodal speech and visual gesture (mSVG) control model for a practical patrol, search, and rescue aerobot Proceedings Article
In: 19th Towards Autonomous Robotic Systems (TAROS) Conference 2018, pp. 423–437, Springer, 2018.
@inproceedings{soton418869,
title = {The multimodal speech and visual gesture (mSVG) control model for a practical patrol, search, and rescue aerobot},
author = {Opeyemi Abioye Ayodeji and Stephen Prior and Trevor Thomas and Peter Saddington and Sarvapali D. Ramchurn},
url = {https://eprints.soton.ac.uk/418869/},
year = {2018},
date = {2018-07-01},
booktitle = {19th Towards Autonomous Robotic Systems (TAROS) Conference 2018},
volume = {10965},
pages = {423–437},
publisher = {Springer},
abstract = {This paper describes a model of the multimodal speech and visual gesture (mSVG) control for aerobots operating at higher nCA autonomy levels, within the context of a patrol, search, and rescue application. The developed mSVG control architecture, its mathematical navigation model, and some high level command operation models were discussed. This was successfully tested using both MATLAB simulation and python based ROS Gazebo UAV simulations. Some limitations were identified, which formed the basis for the further works presented.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper describes a model of the multimodal speech and visual gesture (mSVG) control for aerobots operating at higher nCA autonomy levels, within the context of a patrol, search, and rescue application. The developed mSVG control architecture, its mathematical navigation model, and some high level command operation models were discussed. This was successfully tested using both MATLAB simulation and python based ROS Gazebo UAV simulations. Some limitations were identified, which formed the basis for the further works presented.
71.
Ortega, Andre P; Merrett, Geoff; Ramchurn, Sarvapali
Automated negotiation for opportunistic energy trading between neighbouring wireless sensor networks Proceedings Article
In: 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (31/10/18), 2018.
@inproceedings{soton423060,
title = {Automated negotiation for opportunistic energy trading between neighbouring wireless sensor networks},
author = {Andre P Ortega and Geoff Merrett and Sarvapali Ramchurn},
url = {https://eprints.soton.ac.uk/423060/},
year = {2018},
date = {2018-07-01},
booktitle = {2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (31/10/18)},
abstract = {As the Internet of Things grows, the number of wireless sensor networks deployed in close proximity will continue to increase. By nature, these networks are limited by the battery supply that determines their lifetime and system utility. To counter such a shortcoming, energy harvesting technologies have become increasingly investigated to provide a perpetual energy source; however, new problems arise as a result of their wide spatio-temporal variation. In this paper, we propose opportunistic energy trading, which enables otherwise independent networks to be sustained by sharing resources. Our goal is to provide a novel cooperation model based on negotiation to solve coordination conflicts between energy harvesting wireless sensor networks. Results show that networks are able to satisfy their loads when they agree to cooperate.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
As the Internet of Things grows, the number of wireless sensor networks deployed in close proximity will continue to increase. By nature, these networks are limited by the battery supply that determines their lifetime and system utility. To counter such a shortcoming, energy harvesting technologies have become increasingly investigated to provide a perpetual energy source; however, new problems arise as a result of their wide spatio-temporal variation. In this paper, we propose opportunistic energy trading, which enables otherwise independent networks to be sustained by sharing resources. Our goal is to provide a novel cooperation model based on negotiation to solve coordination conflicts between energy harvesting wireless sensor networks. Results show that networks are able to satisfy their loads when they agree to cooperate.
72.
Ayodeji, Opeyemi Abioye; Prior, Stephen; Thomas, Trevor; Saddington, Peter; Ramchurn, Sarvapali
Quantifying the effects of varying light-visibility and noise-sound levels in practical multimodal speech and visual gesture (mSVG) interaction with aerobots Proceedings Article
In: IEEE International Conference on Applied System Innovation (IEEE ICASI) 2018, pp. 842–845, IEEE, 2018.
@inproceedings{soton418871,
title = {Quantifying the effects of varying light-visibility and noise-sound levels in practical multimodal speech and visual gesture (mSVG) interaction with aerobots},
author = {Opeyemi Abioye Ayodeji and Stephen Prior and Trevor Thomas and Peter Saddington and Sarvapali Ramchurn},
url = {https://eprints.soton.ac.uk/418871/},
year = {2018},
date = {2018-06-01},
booktitle = {IEEE International Conference on Applied System Innovation (IEEE ICASI) 2018},
pages = {842–845},
publisher = {IEEE},
abstract = {This paper discusses the research work conducted to quantify the effective range of lighting levels and ambient noise levels in order to inform the design and development of a multimodal speech and visual gesture (mSVG) control interface for the control of a UAV. Noise level variation from 55 dB to 85 dB is observed under control lab conditions to determine where speech commands for a UAV fails, and to consider why, and possibly suggest a solution around this. Similarly, lighting levels are varied within the control lab condition to determine a range of effective visibility levels. The limitation of this work and some further work from this were also presented.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper discusses the research work conducted to quantify the effective range of lighting levels and ambient noise levels in order to inform the design and development of a multimodal speech and visual gesture (mSVG) control interface for the control of a UAV. Noise level variation from 55 dB to 85 dB is observed under control lab conditions to determine where speech commands for a UAV fails, and to consider why, and possibly suggest a solution around this. Similarly, lighting levels are varied within the control lab condition to determine a range of effective visibility levels. The limitation of this work and some further work from this were also presented.
73.
Garcia, Pedro Garcia; Costanza, Enrico; Verame, Jhim; Nowacka, Diana; Ramchurn, Sarvapali D
Seeing (movement) is believing: the effect of motion on perception of automatic systems performance Journal Article
In: Human-Computer Interaction, pp. 1-51, 2018.
@article{soton422967,
title = {Seeing (movement) is believing: the effect of motion on perception of automatic systems performance},
author = {Pedro Garcia Garcia and Enrico Costanza and Jhim Verame and Diana Nowacka and Sarvapali D Ramchurn},
url = {https://eprints.soton.ac.uk/422967/},
year = {2018},
date = {2018-04-01},
journal = {Human-Computer Interaction},
pages = {1-51},
abstract = {ensuremath<pensuremath>In this article, we report on one lab study and seven follow-up studies on a crowdsourcing platform designed to investigate the potential of animation cues to influence users? perception of two smart systems: a handwriting recognition and a part-of-speech tagging system. Results from the first three studies indicate that animation cues can influence a participant?s perception of both systems? performance. The subsequent three studies, designed to try and identify an explanation for this effect, suggest that this effect is related to the participants? mental model of the smart system. The last two studies were designed to characterize the effect more in detail, and they revealed that different amounts of animation do not seem to create substantial differences and that the effect persists even when the system?s performance decreases, but only when the difference in performance level between the systems being compared is small.ensuremath</pensuremath>},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
ensuremath<pensuremath>In this article, we report on one lab study and seven follow-up studies on a crowdsourcing platform designed to investigate the potential of animation cues to influence users? perception of two smart systems: a handwriting recognition and a part-of-speech tagging system. Results from the first three studies indicate that animation cues can influence a participant?s perception of both systems? performance. The subsequent three studies, designed to try and identify an explanation for this effect, suggest that this effect is related to the participants? mental model of the smart system. The last two studies were designed to characterize the effect more in detail, and they revealed that different amounts of animation do not seem to create substantial differences and that the effect persists even when the system?s performance decreases, but only when the difference in performance level between the systems being compared is small.ensuremath</pensuremath>
74.
Bicego, M.; Farinelli, A.; Grosso, E.; Paolini, D.; Ramchurn, S. D.
On the distinctiveness of the electricity load profile Journal Article
In: Pattern Recognition, vol. 74, no. Supplement C, pp. 317–325, 2018, ISSN: 0031-3203.
@article{BICEGO2018317b,
title = {On the distinctiveness of the electricity load profile},
author = {M. Bicego and A. Farinelli and E. Grosso and D. Paolini and S. D. Ramchurn},
url = {http://www.sciencedirect.com/science/article/pii/S0031320317303904},
doi = {https://doi.org/10.1016/j.patcog.2017.09.039},
issn = {0031-3203},
year = {2018},
date = {2018-01-01},
journal = {Pattern Recognition},
volume = {74},
number = {Supplement C},
pages = {317–325},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
75.
Olabambo, Ifeoluwa Oluwasuji; Malik, Obaid; Zhang, Jie; Ramchurn, Sarvapali
Algorithms for fair load shedding in developing countries Proceedings Article
In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), pp. 1590-1596, 2018.
@inproceedings{soton420541,
title = {Algorithms for fair load shedding in developing countries},
author = {Ifeoluwa Oluwasuji Olabambo and Obaid Malik and Jie Zhang and Sarvapali Ramchurn},
url = {https://eprints.soton.ac.uk/420541/},
year = {2018},
date = {2018-01-01},
booktitle = {Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI)},
pages = {1590-1596},
abstract = {Due to the limited generation capacity of power stations, many developing countries frequently resort to disconnecting large parts of the power grid from supply, a process termed load shedding. During load shedding, many homes are left without electricity, causing them inconvenience and discomfort. In this paper, we present a number of optimization heuristics that focus on pairwise and groupwise fairness, such that households (i.e. agents) are fairly allocated electricity. We evaluate the heuristics against standard fairness metrics in terms of comfort delivered to homes, as well as the number of times they are disconnected from electricity supply. Thus, we establish new benchmarks for fair load shedding schemes.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Due to the limited generation capacity of power stations, many developing countries frequently resort to disconnecting large parts of the power grid from supply, a process termed load shedding. During load shedding, many homes are left without electricity, causing them inconvenience and discomfort. In this paper, we present a number of optimization heuristics that focus on pairwise and groupwise fairness, such that households (i.e. agents) are fairly allocated electricity. We evaluate the heuristics against standard fairness metrics in terms of comfort delivered to homes, as well as the number of times they are disconnected from electricity supply. Thus, we establish new benchmarks for fair load shedding schemes.
76.
Olabambo, Ifeoluwa Oluwasuji; Malik, Obaid; Zhang, Jie; Ramchurn, Sarvapali
Algorithms to manage load shedding events in developing countries Proceedings Article
In: Proceedings of the International Conference on Autonomous and Multi-Agent Systems (AAMAS), pp. 2034-2036, 2018.
@inproceedings{soton420127,
title = {Algorithms to manage load shedding events in developing countries},
author = {Ifeoluwa Oluwasuji Olabambo and Obaid Malik and Jie Zhang and Sarvapali Ramchurn},
url = {https://eprints.soton.ac.uk/420127/},
year = {2018},
date = {2018-01-01},
booktitle = {Proceedings of the International Conference on Autonomous and Multi-Agent Systems (AAMAS)},
pages = {2034-2036},
abstract = {Due to the limited generation capacity of power stations, many developing countries frequently resort to disconnecting large parts of the power grid from supply, a process termed load shedding. This leaves homes without electricity, causing them discomfort and inconvenience. Because fairness is not a priority when shedding load, some homes bear the brunt of these effects. In this paper, we present our ongoing research into considering fairness when shedding load at the household level.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Due to the limited generation capacity of power stations, many developing countries frequently resort to disconnecting large parts of the power grid from supply, a process termed load shedding. This leaves homes without electricity, causing them discomfort and inconvenience. Because fairness is not a priority when shedding load, some homes bear the brunt of these effects. In this paper, we present our ongoing research into considering fairness when shedding load at the household level.
77.
Kiel, Manzano Verame Jhim; Costanza, Enrico; Ramchurn, Sarvapali; Fischer, Joel; Crabtree, Andy; Rodden, Tom; Jennings, Nick
Learning from the veg box: Designing unpredictability in agency delegation Proceedings Article
In: CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, ACM, 2018.
@inproceedings{soton417370,
title = {Learning from the veg box: Designing unpredictability in agency delegation},
author = {Manzano Verame Jhim Kiel and Enrico Costanza and Sarvapali Ramchurn and Joel Fischer and Andy Crabtree and Tom Rodden and Nick Jennings},
url = {https://eprints.soton.ac.uk/417370/},
year = {2018},
date = {2018-01-01},
booktitle = {CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems},
publisher = {ACM},
abstract = {The Internet of Things (IoT) promises to enable applications that foster a more efficient, sustainable, and healthy way of life. If end-users are to take full advantage of these developments we foresee the need for future IoT systems and services to include an element of autonomy and support the delegation of agency to software processes and connected devices. To inform the design of such future technology, we report on a breaching experiment designed to investigate how people integrate an unpredictable service, through the veg box scheme, in everyday life. Findings from our semistructured interviews and a two-week diary study with 11 households reveal that agency delegation must be warranted, that it must be possible to incorporate delegated decisions into everyday activities, and that delegation is subject to constraint. We further discuss design implications on the need to support people?s diverse values, and their coordinative and creative practices.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The Internet of Things (IoT) promises to enable applications that foster a more efficient, sustainable, and healthy way of life. If end-users are to take full advantage of these developments we foresee the need for future IoT systems and services to include an element of autonomy and support the delegation of agency to software processes and connected devices. To inform the design of such future technology, we report on a breaching experiment designed to investigate how people integrate an unpredictable service, through the veg box scheme, in everyday life. Findings from our semistructured interviews and a two-week diary study with 11 households reveal that agency delegation must be warranted, that it must be possible to incorporate delegated decisions into everyday activities, and that delegation is subject to constraint. We further discuss design implications on the need to support people?s diverse values, and their coordinative and creative practices.
78.
Vu, Huan; Aknine, Samir; Ramchurn, Sarvapali D
A Decentralised Approach to Intersection Traffic Management Proceedings Article
In: Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI 2018, July 13-19, 2018, Stockholm, Sweden., pp. 527–533, 2018.
@inproceedings{DBLP:conf/ijcai/VuAR18,
title = {A Decentralised Approach to Intersection Traffic Management},
author = {Huan Vu and Samir Aknine and Sarvapali D Ramchurn},
url = {https://doi.org/10.24963/ijcai.2018/73},
doi = {10.24963/ijcai.2018/73},
year = {2018},
date = {2018-01-01},
booktitle = {Proceedings of the Twenty-Seventh International Joint Conference on
Artificial Intelligence, IJCAI 2018, July 13-19, 2018, Stockholm,
Sweden.},
pages = {527–533},
crossref = {DBLP:conf/ijcai/2018},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
79.
Khan, Md. Mosaddek; -, Long Tran; Ramchurn, Sarvapali D; Jennings, Nicholas R
Speeding Up GDL-Based Message Passing Algorithms for Large-Scale DCOPs Journal Article
In: Comput. J., vol. 61, no. 11, pp. 1639–1666, 2018.
@article{DBLP:journals/cj/KhanTRJ18,
title = {Speeding Up GDL-Based Message Passing Algorithms for Large-Scale DCOPs},
author = {Md. Mosaddek Khan and Long Tran - and Sarvapali D Ramchurn and Nicholas R Jennings},
url = {https://doi.org/10.1093/comjnl/bxy021},
doi = {10.1093/comjnl/bxy021},
year = {2018},
date = {2018-01-01},
journal = {Comput. J.},
volume = {61},
number = {11},
pages = {1639–1666},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
80.
Rigas, Emmanouil S; Karapostolakis, Sotiris; Bassiliades, Nick; Ramchurn, Sarvapali D
EVLibSim: A tool for the simulation of electric vehicles' charging stations using the EVLib library Journal Article
In: Simulation Modelling Practice and Theory, vol. 87, pp. 99–119, 2018.
@article{DBLP:journals/simpra/RigasKBR18,
title = {EVLibSim: A tool for the simulation of electric vehicles' charging
stations using the EVLib library},
author = {Emmanouil S Rigas and Sotiris Karapostolakis and Nick Bassiliades and Sarvapali D Ramchurn},
url = {https://doi.org/10.1016/j.simpat.2018.06.007},
doi = {10.1016/j.simpat.2018.06.007},
year = {2018},
date = {2018-01-01},
journal = {Simulation Modelling Practice and Theory},
volume = {87},
pages = {99–119},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2012
Ebden, Mark; Huynh, Trung Dong; Moreau, Luc; Ramchurn, Sarvapali; Stephen, Roberts
Network analysis on provenance graphs from a crowdsourcing application Proceedings Article
In: Groth, Paul; Frew, James (Ed.): 4th International Provenance and Annotation Workshop, pp. 168–182, 2012.
Abstract | Links | BibTeX | Tags: collabmap, crowdsourcing, densification, evacuation, graph diameters, maps, network analysis, node degree, provenance, provenance graphs
@inproceedings{eps340068,
title = {Network analysis on provenance graphs from a crowdsourcing application},
author = {Mark Ebden and Trung Dong Huynh and Luc Moreau and Sarvapali Ramchurn and Roberts Stephen},
editor = {Paul Groth and James Frew},
url = {http://eprints.soton.ac.uk/340068/},
year = {2012},
date = {2012-01-01},
booktitle = {4th International Provenance and Annotation Workshop},
volume = {7525},
pages = {168–182},
series = {0302-9743},
abstract = {Crowdsourcing has become a popular means for quickly achieving various tasks in large quantities. CollabMap is an online mapping application in which we crowdsource the identification of evacuation routes in residential areas to be used for planning large-scale evacuations. So far, approximately 38,000 micro-tasks have been completed by over 100 contributors. In order to assist with data verification, we introduced provenance tracking into the application, and approximately 5,000 provenance graphs have been generated. They have provided us various insights into the typical characteristics of provenance graphs in the crowdsourcing context. In particular, we have estimated probability distribution functions over three selected characteristics of these provenance graphs: the node degree, the graph diameter, and the densification exponent. We describe methods to define these three characteristics across specific combinations of node types and edge types, and present our findings in this paper. Applications of our methods include rapid comparison of one provenance graph versus another, or of one style of provenance database versus another. Our results also indicate that provenance graphs represent a suitable area of exploitation for existing network analysis tools concerned with modelling, prediction, and the inference of missing nodes and edges.},
keywords = {collabmap, crowdsourcing, densification, evacuation, graph diameters, maps, network analysis, node degree, provenance, provenance graphs},
pubstate = {published},
tppubtype = {inproceedings}
}
Crowdsourcing has become a popular means for quickly achieving various tasks in large quantities. CollabMap is an online mapping application in which we crowdsource the identification of evacuation routes in residential areas to be used for planning large-scale evacuations. So far, approximately 38,000 micro-tasks have been completed by over 100 contributors. In order to assist with data verification, we introduced provenance tracking into the application, and approximately 5,000 provenance graphs have been generated. They have provided us various insights into the typical characteristics of provenance graphs in the crowdsourcing context. In particular, we have estimated probability distribution functions over three selected characteristics of these provenance graphs: the node degree, the graph diameter, and the densification exponent. We describe methods to define these three characteristics across specific combinations of node types and edge types, and present our findings in this paper. Applications of our methods include rapid comparison of one provenance graph versus another, or of one style of provenance database versus another. Our results also indicate that provenance graphs represent a suitable area of exploitation for existing network analysis tools concerned with modelling, prediction, and the inference of missing nodes and edges.
Matthews, Tim; Ramchurn, Sarvapali; Chalkiadakis, Georgios
Competing with humans at fantasy football: team formation in large partially-observable domains Proceedings Article
In: Proceedings of the Twenty-Sixth Conference on Artificial Intelligence, pp. 1394–1400, Association for the Advancement of Artificial Intelligence, 2012.
Abstract | Links | BibTeX | Tags: multi-agent systems, optimisation, sequential decision making, team formation
@inproceedings{eps340382,
title = {Competing with humans at fantasy football: team formation in large partially-observable domains},
author = {Tim Matthews and Sarvapali Ramchurn and Georgios Chalkiadakis},
url = {http://eprints.soton.ac.uk/340382/},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings of the Twenty-Sixth Conference on Artificial Intelligence},
pages = {1394–1400},
publisher = {Association for the Advancement of Artificial Intelligence},
abstract = {We present the first real-world benchmark for sequentially optimal team formation, working within the framework of a class of online football prediction games known as Fantasy Football. We model the problem as a Bayesian reinforcement learning one, where the action space is exponential in the number of players and where the decision maker?s beliefs are over multiple characteristics of each footballer. We then exploit domain knowledge to construct computationally tractable solution techniques in order to build a competitive automated Fantasy Football manager. Thus, we are able to establish the baseline performance in this domain, even without complete information on footballers? performances (accessible to human managers), showing that our agent is able to rank at around the top percentile when pitched against 2.5M human players},
keywords = {multi-agent systems, optimisation, sequential decision making, team formation},
pubstate = {published},
tppubtype = {inproceedings}
}
We present the first real-world benchmark for sequentially optimal team formation, working within the framework of a class of online football prediction games known as Fantasy Football. We model the problem as a Bayesian reinforcement learning one, where the action space is exponential in the number of players and where the decision maker?s beliefs are over multiple characteristics of each footballer. We then exploit domain knowledge to construct computationally tractable solution techniques in order to build a competitive automated Fantasy Football manager. Thus, we are able to establish the baseline performance in this domain, even without complete information on footballers? performances (accessible to human managers), showing that our agent is able to rank at around the top percentile when pitched against 2.5M human players
Miller, Sam; Ramchurn, Sarvapali D; Rogers, Alex
Optimal Decentralised Dispatch of Embedded Generation in the Smart Grid Journal Article
In: In Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2012.
Abstract | Links | BibTeX | Tags: Energy, human-agent interaction, smart grid
@article{eps273142,
title = {Optimal Decentralised Dispatch of Embedded Generation in the Smart Grid},
author = {Sam Miller and Sarvapali D Ramchurn and Alex Rogers},
url = {http://eprints.soton.ac.uk/273142/},
year = {2012},
date = {2012-01-01},
booktitle = {Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS)},
journal = {In Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS)},
abstract = {Distribution network operators face a number of challenges; capacity constrained networks, and balancing electricity demand with generation from intermittent renewable resources. Thus, there is an increasing need for scalable approaches to facilitate optimal dispatch in the distribution network. To this end, we cast the optimal dispatch problem as a decentralised agent-based coordination problem and formalise it as a DCOP. We show how this can be decomposed as a factor graph and solved in a decentralised manner using algorithms based on the generalised distributive law; in particular, the max-sum algorithm. We go on to show that max-sum applied na?vely in this setting performs a large number of redundant computations. To address this issue, we present a novel decentralised message passing algorithm using dynamic programming that outperforms max-sum by pruning the search space. We empirically evaluate our algorithm using real distribution network data, showing that it outperforms (in terms of computational time and total size of messages sent) both a centralised approach, which uses IBM?s ILOG CPLEX 12.2, and max-sum, for large networks.},
keywords = {Energy, human-agent interaction, smart grid},
pubstate = {published},
tppubtype = {article}
}
Distribution network operators face a number of challenges; capacity constrained networks, and balancing electricity demand with generation from intermittent renewable resources. Thus, there is an increasing need for scalable approaches to facilitate optimal dispatch in the distribution network. To this end, we cast the optimal dispatch problem as a decentralised agent-based coordination problem and formalise it as a DCOP. We show how this can be decomposed as a factor graph and solved in a decentralised manner using algorithms based on the generalised distributive law; in particular, the max-sum algorithm. We go on to show that max-sum applied na?vely in this setting performs a large number of redundant computations. To address this issue, we present a novel decentralised message passing algorithm using dynamic programming that outperforms max-sum by pruning the search space. We empirically evaluate our algorithm using real distribution network data, showing that it outperforms (in terms of computational time and total size of messages sent) both a centralised approach, which uses IBM?s ILOG CPLEX 12.2, and max-sum, for large networks.
Ramchurn, Sarvapali; Vytelingum, Perukrishnen; Rogers, Alex; Jennings, Nicholas R.
Putting the Smarts into the Smart Grid: A Grand Challenge for Artificial Intelligence Journal Article
In: Communications of the ACM, vol. 55, no. 4, pp. 86–97, 2012.
Abstract | Links | BibTeX | Tags: electricity, Energy, smart grid, smart home
@article{eps272606,
title = {Putting the Smarts into the Smart Grid: A Grand Challenge for Artificial Intelligence},
author = {Sarvapali Ramchurn and Perukrishnen Vytelingum and Alex Rogers and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/272606/},
year = {2012},
date = {2012-01-01},
journal = {Communications of the ACM},
volume = {55},
number = {4},
pages = {86–97},
publisher = {ACM},
abstract = {The phenomenal growth in material wealth experienced in developed countries throughout the twentieth century has largely been driven by the availability of cheap energy derived from fossil fuels (originally coal, then oil, and most recently natural gas). However, the continued availability of this cheap energy cannot be taken for granted given the growing concern that increasing demand for these fuels (and particularly, demand for oil) will outstrip our ability to produce them (so called `peak oil'). Many mature oil and gas fields around the world have already peaked and their annual production is now steadily declining. Predictions of when world oil production will peak vary between 0-20 years into the future, but even the most conservative estimates provide little scope for complacency given the significant price increases that peak oil is likely to precipitate. Furthermore, many of the oil and gas reserves that do remain are in environmentally or politically sensitive regions of the world where threats to supply create increased price volatility (as evidenced by the 2010 Deepwater Horizon disaster and 2011 civil unrest in the Middle East). Finally, the growing consensus on the long term impact of carbon emissions from burning fossil fuels suggests that even if peak oil is avoided, and energy security assured, a future based on fossil fuel use will expose regions of the world to damaging climate change that will make the lives of many of the world's poorest people even harder.},
keywords = {electricity, Energy, smart grid, smart home},
pubstate = {published},
tppubtype = {article}
}
The phenomenal growth in material wealth experienced in developed countries throughout the twentieth century has largely been driven by the availability of cheap energy derived from fossil fuels (originally coal, then oil, and most recently natural gas). However, the continued availability of this cheap energy cannot be taken for granted given the growing concern that increasing demand for these fuels (and particularly, demand for oil) will outstrip our ability to produce them (so called `peak oil'). Many mature oil and gas fields around the world have already peaked and their annual production is now steadily declining. Predictions of when world oil production will peak vary between 0-20 years into the future, but even the most conservative estimates provide little scope for complacency given the significant price increases that peak oil is likely to precipitate. Furthermore, many of the oil and gas reserves that do remain are in environmentally or politically sensitive regions of the world where threats to supply create increased price volatility (as evidenced by the 2010 Deepwater Horizon disaster and 2011 civil unrest in the Middle East). Finally, the growing consensus on the long term impact of carbon emissions from burning fossil fuels suggests that even if peak oil is avoided, and energy security assured, a future based on fossil fuel use will expose regions of the world to damaging climate change that will make the lives of many of the world's poorest people even harder.
Ramchurn, Sarvapali D.; Gerding, Enrico; Jennings, N. R.; Hu, Jun
Practical distributed coalition formation via heuristic negotiation in social networks Proceedings Article
In: Fifth International Workshop on Optimisation in Multi-Agent Systems (OPTMAS), 2012.
Abstract | Links | BibTeX | Tags: mas, multi-agent systems
@inproceedings{eps344492,
title = {Practical distributed coalition formation via heuristic negotiation in social networks},
author = {Sarvapali D. Ramchurn and Enrico Gerding and N. R. Jennings and Jun Hu},
url = {http://eprints.soton.ac.uk/344492/},
year = {2012},
date = {2012-01-01},
booktitle = {Fifth International Workshop on Optimisation in Multi-Agent Systems (OPTMAS)},
abstract = {We present a novel framework for decentralised coalition formation in social networks, where agents can form coalitions through bilateral negotiations with their neighbours. Specifically, we present a practical negotiation protocol and decision functions that enable agents to form coalitions with agents beyond their peers. Building on this, we establish baseline negotiation strategies which we empirically show to be efficient (agreements are reached in few negotiation rounds) and effective (agreements have high utility compared to a centralised approach) on a variety of network topologies. Moreover, we show that the average degree of social networks can significantly affect the performance of these strategies.},
keywords = {mas, multi-agent systems},
pubstate = {published},
tppubtype = {inproceedings}
}
We present a novel framework for decentralised coalition formation in social networks, where agents can form coalitions through bilateral negotiations with their neighbours. Specifically, we present a practical negotiation protocol and decision functions that enable agents to form coalitions with agents beyond their peers. Building on this, we establish baseline negotiation strategies which we empirically show to be efficient (agreements are reached in few negotiation rounds) and effective (agreements have high utility compared to a centralised approach) on a variety of network topologies. Moreover, we show that the average degree of social networks can significantly affect the performance of these strategies.
Richardson, Darren P.; Costanza, Enrico; Ramchurn, Sarvapali D.
Evaluating semi-automatic annotation of domestic energy consumption as a memory aid Proceedings Article
In: UbiComp '12 Proceedings of the 2012 ACM Conference on Ubiquitous Computing, pp. 613–614, 2012.
Abstract | Links | BibTeX | Tags: Energy, hai, home energy management, human-agent interaction
@inproceedings{eps349083,
title = {Evaluating semi-automatic annotation of domestic energy consumption as a memory aid},
author = {Darren P. Richardson and Enrico Costanza and Sarvapali D. Ramchurn},
url = {http://eprints.soton.ac.uk/349083/},
year = {2012},
date = {2012-01-01},
booktitle = {UbiComp '12 Proceedings of the 2012 ACM Conference on Ubiquitous Computing},
pages = {613–614},
abstract = {Frequent feedback about energy consumption can help conservation, one of the current global challenges. Such feedback is most helpful if users can relate it to their own day-to-day activities. In earlier work we showed that manual annotation of domestic energy consumption logs aids users to make such connection and discover patterns they were not aware of. In this poster we report how we augmented manual annotation with machine learning classification techniques. We propose the design of a lab study to evaluate the system, extending methods used to evaluate context aware memory aids, and we present the results of a pilot with 5 participants.},
keywords = {Energy, hai, home energy management, human-agent interaction},
pubstate = {published},
tppubtype = {inproceedings}
}
Frequent feedback about energy consumption can help conservation, one of the current global challenges. Such feedback is most helpful if users can relate it to their own day-to-day activities. In earlier work we showed that manual annotation of domestic energy consumption logs aids users to make such connection and discover patterns they were not aware of. In this poster we report how we augmented manual annotation with machine learning classification techniques. We propose the design of a lab study to evaluate the system, extending methods used to evaluate context aware memory aids, and we present the results of a pilot with 5 participants.
Rogers, Alex; Ramchurn, Sarvapali; Jennings, Nicholas R.
Delivering the smart grid: Challenges for autonomous agents and multi-agent systems research Proceedings Article
In: Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12), pp. 2166–2172, 2012.
Abstract | Links | BibTeX | Tags: electricity, Energy, home energy management
@inproceedings{eps337560,
title = {Delivering the smart grid: Challenges for autonomous agents and multi-agent systems research},
author = {Alex Rogers and Sarvapali Ramchurn and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/337560/},
year = {2012},
date = {2012-01-01},
booktitle = {Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12)},
pages = {2166–2172},
abstract = {Restructuring electricity grids to meet the increased demand caused by the electrification of transport and heating, while making greater use of intermittent renewable energy sources, represents one of the greatest engineering challenges of our day. This modern electric- ity grid, in which both electricity and information flow in two directions between large numbers of widely dis- tributed suppliers and generators – commonly termed the ?smart grid? – represents a radical reengineering of infrastructure which has changed little over the last hundred years. However, the autonomous behaviour expected of the smart grid, its distributed nature, and the existence of multiple stakeholders each with their own incentives and interests, challenges existing engineering approaches. In this challenge paper, we describe why we believe that artificial intelligence, and particularly, the fields of autonomous agents and multi-agent systems are essential for delivering the smart grid as it is envisioned. We present some recent work in this area and describe many of the challenges that still remain.},
keywords = {electricity, Energy, home energy management},
pubstate = {published},
tppubtype = {inproceedings}
}
Restructuring electricity grids to meet the increased demand caused by the electrification of transport and heating, while making greater use of intermittent renewable energy sources, represents one of the greatest engineering challenges of our day. This modern electric- ity grid, in which both electricity and information flow in two directions between large numbers of widely dis- tributed suppliers and generators – commonly termed the ?smart grid? – represents a radical reengineering of infrastructure which has changed little over the last hundred years. However, the autonomous behaviour expected of the smart grid, its distributed nature, and the existence of multiple stakeholders each with their own incentives and interests, challenges existing engineering approaches. In this challenge paper, we describe why we believe that artificial intelligence, and particularly, the fields of autonomous agents and multi-agent systems are essential for delivering the smart grid as it is envisioned. We present some recent work in this area and describe many of the challenges that still remain.
Truong, Ngoc Cuong; Tran-Thanh, Long; Costanza, Enrico; Ramchurn, Sarvapali D.
Predicting energy consumption activities for home energy management Proceedings Article
In: Agent Technologies for Energy Systems (ATES 2012), 2012.
Links | BibTeX | Tags: Energy, human-agent interaction, smart grid, smart home
@inproceedings{eps339215,
title = {Predicting energy consumption activities for home energy management},
author = {Ngoc Cuong Truong and Long Tran-Thanh and Enrico Costanza and Sarvapali D. Ramchurn},
url = {http://eprints.soton.ac.uk/339215/},
year = {2012},
date = {2012-01-01},
booktitle = {Agent Technologies for Energy Systems (ATES 2012)},
keywords = {Energy, human-agent interaction, smart grid, smart home},
pubstate = {published},
tppubtype = {inproceedings}
}
Voice, Thomas; Ramchurn, Sarvapali; Jennings, Nick
On coalition formation with sparse synergies Proceedings Article
In: Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), pp. 223–230, 2012.
@inproceedings{eps273083,
title = {On coalition formation with sparse synergies},
author = {Thomas Voice and Sarvapali Ramchurn and Nick Jennings},
url = {http://eprints.soton.ac.uk/273083/},
year = {2012},
date = {2012-01-01},
booktitle = {Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS)},
pages = {223–230},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Simpson, Edwin; Reece, Steven; Penta, Antonio; Ramchurn, Sarvapali D
Using a Bayesian Model to Combine LDA Features with Crowdsourced Responses Proceedings Article
In: Proceedings of The Twenty-First Text REtrieval Conference, TREC 2012, Gaithersburg, Maryland, USA, November 6-9, 2012, 2012.
@inproceedings{DBLP:conf/trec/SimpsonRPR12,
title = {Using a Bayesian Model to Combine LDA Features with Crowdsourced
Responses},
author = {Edwin Simpson and Steven Reece and Antonio Penta and Sarvapali D Ramchurn},
url = {http://trec.nist.gov/pubs/trec21/papers/HAC.crowd.final.pdf},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings of The Twenty-First Text REtrieval Conference, TREC
2012, Gaithersburg, Maryland, USA, November 6-9, 2012},
crossref = {DBLP:conf/trec/2012},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
2011
Alam, Muddasser; Rogers, Alex; Ramchurn, Sarvapali
A negotiation protocol for multiple interdependent issues negotiation over energy exchange Proceedings Article
In: IJCAI Workshop on AI for an Intelligent Planet, 2011, (Event Dates: July-16).
Abstract | Links | BibTeX | Tags: Multiagent Systems Negotiation Protocol Rules of encounter Multiissue Negotiation Interdependent multi issue negotiation
@inproceedings{eps272479,
title = {A negotiation protocol for multiple interdependent issues negotiation over energy exchange},
author = {Muddasser Alam and Alex Rogers and Sarvapali Ramchurn},
url = {http://eprints.soton.ac.uk/272479/},
year = {2011},
date = {2011-01-01},
booktitle = {IJCAI Workshop on AI for an Intelligent Planet},
abstract = {We present a novel negotiation protocol to facilitate energy exchange between off-grid homes that are equipped with renewable energy generation and electricity storage. Our solution imposes additional constraints on negotiation such that it reduces a complex interdependent multi-issue problem to one that is tractable. We prove that using our protocol, agents can reach a Pareto-optimal, dominant strategy equilibrium in a decentralized and timely fashion. We empirically evaluate our approach in a realistic setting. In this case, we show that energy exchange can be useful in reducing the capacity of the energy storage devices in homes by close to 40%},
note = {Event Dates: July-16},
keywords = {Multiagent Systems Negotiation Protocol Rules of encounter Multiissue Negotiation Interdependent multi issue negotiation},
pubstate = {published},
tppubtype = {inproceedings}
}
We present a novel negotiation protocol to facilitate energy exchange between off-grid homes that are equipped with renewable energy generation and electricity storage. Our solution imposes additional constraints on negotiation such that it reduces a complex interdependent multi-issue problem to one that is tractable. We prove that using our protocol, agents can reach a Pareto-optimal, dominant strategy equilibrium in a decentralized and timely fashion. We empirically evaluate our approach in a realistic setting. In this case, we show that energy exchange can be useful in reducing the capacity of the energy storage devices in homes by close to 40%
Macarthur, Kathryn; Stranders, Ruben; Ramchurn, Sarvapali; Jennings, Nick
A Distributed Anytime Algorithm for Dynamic Task Allocation in Multi-Agent Systems Proceedings Article
In: Twenty-Fifth Conference on Artificial Intelligence (AAAI), pp. 701–706, AAAI Press, 2011, (Event Dates: August 7-11, 2011).
Abstract | Links | BibTeX | Tags: mas, Multi-agent scheduling, multi-agent systems
@inproceedings{eps272233,
title = {A Distributed Anytime Algorithm for Dynamic Task Allocation in Multi-Agent Systems},
author = {Kathryn Macarthur and Ruben Stranders and Sarvapali Ramchurn and Nick Jennings},
url = {http://eprints.soton.ac.uk/272233/},
year = {2011},
date = {2011-01-01},
booktitle = {Twenty-Fifth Conference on Artificial Intelligence (AAAI)},
pages = {701–706},
publisher = {AAAI Press},
abstract = {We introduce a novel distributed algorithm for multi-agent task allocation problems where the sets of tasks and agents constantly change over time. We build on an existing anytime algorithm (fast-max-sum), and give it significant new capa- bilities: namely, an online pruning procedure that simplifies the problem, and a branch-and-bound technique that reduces the search space. This allows us to scale to problems with hundreds of tasks and agents. We empirically evaluate our algorithm against established benchmarks and find that, even in such large environments, a solution is found up to 31% faster, and with up to 23% more utility, than state-of-the-art approximation algorithms. In addition, our algorithm sends up to 30% fewer messages than current approaches when the set of agents or tasks changes.},
note = {Event Dates: August 7-11, 2011},
keywords = {mas, Multi-agent scheduling, multi-agent systems},
pubstate = {published},
tppubtype = {inproceedings}
}
We introduce a novel distributed algorithm for multi-agent task allocation problems where the sets of tasks and agents constantly change over time. We build on an existing anytime algorithm (fast-max-sum), and give it significant new capa- bilities: namely, an online pruning procedure that simplifies the problem, and a branch-and-bound technique that reduces the search space. This allows us to scale to problems with hundreds of tasks and agents. We empirically evaluate our algorithm against established benchmarks and find that, even in such large environments, a solution is found up to 31% faster, and with up to 23% more utility, than state-of-the-art approximation algorithms. In addition, our algorithm sends up to 30% fewer messages than current approaches when the set of agents or tasks changes.
Macarthur, Kathryn; Vinyals, Meritxell; Farinelli, Alessandro; Ramchurn, Sarvapali; Jennings, Nick
Decentralised Parallel Machine Scheduling for Multi-Agent Task Allocation Proceedings Article
In: Fourth International Workshop on Optimisation in Multi-Agent Systems, 2011, (Event Dates: May 3, 2011).
Abstract | Links | BibTeX | Tags: mas, Multi-agent scheduling, multi-agent systems
@inproceedings{eps272234,
title = {Decentralised Parallel Machine Scheduling for Multi-Agent Task Allocation},
author = {Kathryn Macarthur and Meritxell Vinyals and Alessandro Farinelli and Sarvapali Ramchurn and Nick Jennings},
url = {http://eprints.soton.ac.uk/272234/},
year = {2011},
date = {2011-01-01},
booktitle = {Fourth International Workshop on Optimisation in Multi-Agent Systems},
abstract = {Multi-agent task allocation problems pervade a wide range of real-world applications, such as search and rescue in disaster manage- ment, or grid computing. In these applications, where agents are given tasks to perform in parallel, it is often the case that the performance of all agents is judged based on the time taken by the slowest agent to complete its tasks. Hence, efficient distribution of tasks across het- erogeneous agents is important to ensure a short completion time. An equivalent problem to this can be found in operations research, and is known as scheduling jobs on unrelated parallel machines (also known as Rensuremath|ensuremath|Cmax). In this paper, we draw parallels between unrelated parallel machine scheduling and multi-agent task allocation problems, and, in so doing, we present the decentralised task distribution algorithm (DTDA), the first decentralised solution to Rensuremath|ensuremath|Cmax. Empirical evaluation of the DTDA is shown to generate solutions within 86?97% of the optimal on sparse graphs, in the best case, whilst providing a very good estimate (within 1%) of the global solution at each agent.},
note = {Event Dates: May 3, 2011},
keywords = {mas, Multi-agent scheduling, multi-agent systems},
pubstate = {published},
tppubtype = {inproceedings}
}
Multi-agent task allocation problems pervade a wide range of real-world applications, such as search and rescue in disaster manage- ment, or grid computing. In these applications, where agents are given tasks to perform in parallel, it is often the case that the performance of all agents is judged based on the time taken by the slowest agent to complete its tasks. Hence, efficient distribution of tasks across het- erogeneous agents is important to ensure a short completion time. An equivalent problem to this can be found in operations research, and is known as scheduling jobs on unrelated parallel machines (also known as Rensuremath|ensuremath|Cmax). In this paper, we draw parallels between unrelated parallel machine scheduling and multi-agent task allocation problems, and, in so doing, we present the decentralised task distribution algorithm (DTDA), the first decentralised solution to Rensuremath|ensuremath|Cmax. Empirical evaluation of the DTDA is shown to generate solutions within 86?97% of the optimal on sparse graphs, in the best case, whilst providing a very good estimate (within 1%) of the global solution at each agent.
Osborne, Michael A.; Rogers, Alex; Roberts, Stephen J.; Ramchurn, Sarvapali D.; Jennings, Nicholas R.
Gaussian Processes for Time Series Prediction Book Section
In: Bayesian Time Series Models, pp. 341–360, Cambridge University Press, 2011, (Chapter: 16).
Links | BibTeX | Tags: machine learning, mas
@incollection{eps272746,
title = {Gaussian Processes for Time Series Prediction},
author = {Michael A. Osborne and Alex Rogers and Stephen J. Roberts and Sarvapali D. Ramchurn and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/272746/},
year = {2011},
date = {2011-01-01},
booktitle = {Bayesian Time Series Models},
pages = {341–360},
publisher = {Cambridge University Press},
note = {Chapter: 16},
keywords = {machine learning, mas},
pubstate = {published},
tppubtype = {incollection}
}
Ramchurn, Sarvapali; Vytelingum, Perukrishnen; Rogers, Alex; Jennings, Nick
Agent-based homeostatic control for green energy in the smart grid Journal Article
In: ACM Transactions on Intelligent Systems and Technology, vol. 2, no. 4, pp. 35:1–35:28, 2011.
Abstract | Links | BibTeX | Tags: Energy, mas, multi-agent systems
@article{eps272015,
title = {Agent-based homeostatic control for green energy in the smart grid},
author = {Sarvapali Ramchurn and Perukrishnen Vytelingum and Alex Rogers and Nick Jennings},
url = {http://eprints.soton.ac.uk/272015/},
year = {2011},
date = {2011-01-01},
journal = {ACM Transactions on Intelligent Systems and Technology},
volume = {2},
number = {4},
pages = {35:1–35:28},
abstract = {With dwindling non-renewable energy reserves and the adverse effects of climate change, the development of the smart electricity grid is seen as key to solving global energy security issues and to reducing carbon emissions. In this respect, there is a growing need to integrate renewable (or green) energy sources in the grid. However, the intermittency of these energy sources requires that demand must also be made more responsive to changes in supply, and a number of smart grid technologies are being developed, such as high-capacity batteries and smart meters for the home, to enable consumers to be more responsive to conditions on the grid in real-time. Traditional solutions based on these technologies, however, tend to ignore the fact that individual consumers will behave in such a way that best satisfies their own preferences to use or store energy (as opposed to that of the supplier or the grid operator). Hence, in practice, it is unclear how these solutions will cope with large numbers of consumers using their devices in this way. Against this background, in this paper, we develop novel control mechanisms based on the use of autonomous agents to better incorporate consumer preferences in managing demand. These agents, residing on consumers' smart meters, can both communicate with the grid and optimise their owner's energy consumption to satisfy their preferences. More specifically, we provide a novel control mechanism that models and controls a system comprising of a green energy supplier operating within the grid and a number of individual homes (each possibly owning a storage device). This control mechanism is based on the concept of homeostasis whereby control signals are sent to individual components of a system, based on their continuous feedback, in order to change their state so that the system may reach a stable equilibrium. Thus, we define a new carbon-based pricing mechanism for this green energy supplier that takes advantage of carbon-intensity signals available on the internet in order to provide real-time pricing. The pricing scheme is designed in such a way that it can be readily implemented using existing communication technologies and is easily understandable by consumers. Building upon this, we develop new control signals that the supplier can use to incentivise agents to shift demand (using their storage device) to times when green energy is available. Moreover, we show how these signals can be adapted according to changes in supply and to various degrees of penetration of storage in the system. We empirically evaluate our system and show that, when all homes are equipped with storage devices, the supplier can significantly reduce its reliance on other carbon-emitting power sources to cater for its own shortfalls. By so doing, the supplier reduces the carbon emission of the system by up to 25% while the consumer reduces its costs by up to 14.5%. Finally, we demonstrate that our homeostatic control mechanism is not sensitive to small prediction errors and the supplier is incentivised to accurately predict its green production to minimise costs.},
keywords = {Energy, mas, multi-agent systems},
pubstate = {published},
tppubtype = {article}
}
With dwindling non-renewable energy reserves and the adverse effects of climate change, the development of the smart electricity grid is seen as key to solving global energy security issues and to reducing carbon emissions. In this respect, there is a growing need to integrate renewable (or green) energy sources in the grid. However, the intermittency of these energy sources requires that demand must also be made more responsive to changes in supply, and a number of smart grid technologies are being developed, such as high-capacity batteries and smart meters for the home, to enable consumers to be more responsive to conditions on the grid in real-time. Traditional solutions based on these technologies, however, tend to ignore the fact that individual consumers will behave in such a way that best satisfies their own preferences to use or store energy (as opposed to that of the supplier or the grid operator). Hence, in practice, it is unclear how these solutions will cope with large numbers of consumers using their devices in this way. Against this background, in this paper, we develop novel control mechanisms based on the use of autonomous agents to better incorporate consumer preferences in managing demand. These agents, residing on consumers' smart meters, can both communicate with the grid and optimise their owner's energy consumption to satisfy their preferences. More specifically, we provide a novel control mechanism that models and controls a system comprising of a green energy supplier operating within the grid and a number of individual homes (each possibly owning a storage device). This control mechanism is based on the concept of homeostasis whereby control signals are sent to individual components of a system, based on their continuous feedback, in order to change their state so that the system may reach a stable equilibrium. Thus, we define a new carbon-based pricing mechanism for this green energy supplier that takes advantage of carbon-intensity signals available on the internet in order to provide real-time pricing. The pricing scheme is designed in such a way that it can be readily implemented using existing communication technologies and is easily understandable by consumers. Building upon this, we develop new control signals that the supplier can use to incentivise agents to shift demand (using their storage device) to times when green energy is available. Moreover, we show how these signals can be adapted according to changes in supply and to various degrees of penetration of storage in the system. We empirically evaluate our system and show that, when all homes are equipped with storage devices, the supplier can significantly reduce its reliance on other carbon-emitting power sources to cater for its own shortfalls. By so doing, the supplier reduces the carbon emission of the system by up to 25% while the consumer reduces its costs by up to 14.5%. Finally, we demonstrate that our homeostatic control mechanism is not sensitive to small prediction errors and the supplier is incentivised to accurately predict its green production to minimise costs.
Ramchurn, Sarvapali; Vytelingum, Perukrishnen; Rogers, Alex; Jennings, Nick
Agent-based control for decentralised demand side management in the smart grid Proceedings Article
In: The Tenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), pp. 5–12, 2011.
Abstract | Links | BibTeX | Tags: agent-based control, agents, demand-side management electricity, Energy, multi-agent systems
@inproceedings{eps271985,
title = {Agent-based control for decentralised demand side management in the smart grid},
author = {Sarvapali Ramchurn and Perukrishnen Vytelingum and Alex Rogers and Nick Jennings},
url = {http://eprints.soton.ac.uk/271985/},
year = {2011},
date = {2011-01-01},
booktitle = {The Tenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011)},
pages = {5–12},
abstract = {Central to the vision of the smart grid is the deployment of smart meters that will allow autonomous software agents, representing the consumers, to optimise their use of devices and heating in the smart home while interacting with the grid. However, without some form of coordination, the population of agents may end up with overly-homogeneous optimised consumption patterns that may generate significant peaks in demand in the grid. These peaks, in turn, reduce the efficiency of the overall system, increase carbon emissions, and may even, in the worst case, cause blackouts. Hence, in this paper, we introduce a novel model of a Decentralised Demand Side Management (DDSM) mechanism that allows agents, by adapting the deferment of their loads based on grid prices, to coordinate in a decentralised manner. Specifically, using average UK consumption profiles for 26M homes, we demonstrate that, through an emergent coordination of the agents, the peak demand of domestic consumers in the grid can be reduced by up to 17% and carbon emissions by up to 6%. We also show that our DDSM mechanism is robust to the increasing electrification of heating in UK homes (i.e. it exhibits a similar efficiency).},
keywords = {agent-based control, agents, demand-side management electricity, Energy, multi-agent systems},
pubstate = {published},
tppubtype = {inproceedings}
}
Central to the vision of the smart grid is the deployment of smart meters that will allow autonomous software agents, representing the consumers, to optimise their use of devices and heating in the smart home while interacting with the grid. However, without some form of coordination, the population of agents may end up with overly-homogeneous optimised consumption patterns that may generate significant peaks in demand in the grid. These peaks, in turn, reduce the efficiency of the overall system, increase carbon emissions, and may even, in the worst case, cause blackouts. Hence, in this paper, we introduce a novel model of a Decentralised Demand Side Management (DDSM) mechanism that allows agents, by adapting the deferment of their loads based on grid prices, to coordinate in a decentralised manner. Specifically, using average UK consumption profiles for 26M homes, we demonstrate that, through an emergent coordination of the agents, the peak demand of domestic consumers in the grid can be reduced by up to 17% and carbon emissions by up to 6%. We also show that our DDSM mechanism is robust to the increasing electrification of heating in UK homes (i.e. it exhibits a similar efficiency).
Stranders, Ruben; Ramchurn, Sarvapali; Shi, Bing; Jennings, Nick
CollabMap: Augmenting Maps using the Wisdom of Crowds Proceedings Article
In: Third Human Computation Workshop, 2011.
Links | BibTeX | Tags: Disaster Management, human-agent interaction, mas, multi-agent systems
@inproceedings{eps272478,
title = {CollabMap: Augmenting Maps using the Wisdom of Crowds},
author = {Ruben Stranders and Sarvapali Ramchurn and Bing Shi and Nick Jennings},
url = {http://eprints.soton.ac.uk/272478/},
year = {2011},
date = {2011-01-01},
booktitle = {Third Human Computation Workshop},
keywords = {Disaster Management, human-agent interaction, mas, multi-agent systems},
pubstate = {published},
tppubtype = {inproceedings}
}
Voice, Thomas; Vytelingum, Perukrishnen; Ramchurn, Sarvapali; Rogers, Alex; Jennings, Nick
Decentralised Control of Micro-Storage in the Smart Grid Proceedings Article
In: AAAI-11: Twenty-Fifth Conference on Artificial Intelligence, pp. 1421–1426, 2011, (Event Dates: August 7?11, 2011).
Abstract | Links | BibTeX | Tags: electricity, Energy, smart grid
@inproceedings{eps272262,
title = {Decentralised Control of Micro-Storage in the Smart Grid},
author = {Thomas Voice and Perukrishnen Vytelingum and Sarvapali Ramchurn and Alex Rogers and Nick Jennings},
url = {http://eprints.soton.ac.uk/272262/},
year = {2011},
date = {2011-01-01},
booktitle = {AAAI-11: Twenty-Fifth Conference on Artificial Intelligence},
pages = {1421–1426},
abstract = {In this paper, we propose a novel decentralised control mechanism to manage micro-storage in the smart grid. Our approach uses an adaptive pricing scheme that energy suppliers apply to home smart agents controlling micro-storage devices. In particular, we prove that the interaction between a supplier using our pricing scheme and the actions of selfish micro-storage agents forms a globally stable feedback loop that converges to an efficient equilibrium. We further propose a market strategy that allows the supplier to reduce wholesale purchasing costs without increasing the uncertainty and variance for its aggregate consumer demand. Moreover, we empirically evaluate our mechanism (based on the UK grid data) and show that it yields savings of up to 16% in energy cost for consumers using storage devices with average capacity 10 kWh. Furthermore, we show that it is robust against extreme system changes.},
note = {Event Dates: August 7?11, 2011},
keywords = {electricity, Energy, smart grid},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, we propose a novel decentralised control mechanism to manage micro-storage in the smart grid. Our approach uses an adaptive pricing scheme that energy suppliers apply to home smart agents controlling micro-storage devices. In particular, we prove that the interaction between a supplier using our pricing scheme and the actions of selfish micro-storage agents forms a globally stable feedback loop that converges to an efficient equilibrium. We further propose a market strategy that allows the supplier to reduce wholesale purchasing costs without increasing the uncertainty and variance for its aggregate consumer demand. Moreover, we empirically evaluate our mechanism (based on the UK grid data) and show that it yields savings of up to 16% in energy cost for consumers using storage devices with average capacity 10 kWh. Furthermore, we show that it is robust against extreme system changes.
Vytelingum, Perukrishnen; Voice, Thomas; Ramchurn, Sarvapali; Rogers, Alex; Jennings, Nick
Theoretical and practical foundations of large-scale agent-based micro-storage in the smart grid Journal Article
In: Journal of Artificial Intelligence Research, vol. 42, pp. 765–813, 2011, (AAMAS 2010 iRobot Best Paper Award).
Abstract | Links | BibTeX | Tags: agents, Energy, mas, multi-agent systems, provenance
@article{eps272961,
title = {Theoretical and practical foundations of large-scale agent-based micro-storage in the smart grid},
author = {Perukrishnen Vytelingum and Thomas Voice and Sarvapali Ramchurn and Alex Rogers and Nick Jennings},
url = {http://eprints.soton.ac.uk/272961/},
year = {2011},
date = {2011-01-01},
journal = {Journal of Artificial Intelligence Research},
volume = {42},
pages = {765–813},
abstract = {In this paper, we present a novel decentralised management technique that allows electricity micro-storage devices, deployed within individual homes as part of a smart electricity grid, to converge to profitable and efficient behaviours. Specifically, we propose the use of software agents, residing on the users' smart meters, to automate and optimise the charging cycle of micro-storage devices in the home to minimise its costs, and we present a study of both the theoretical underpinnings and the implications of a practical solution, of using software agents for such micro-storage management. First, by formalising the strategic choice each agent makes in deciding when to charge its battery, we develop a game-theoretic framework within which we can analyse the competitive equilibria of an electricity grid populated by such agents and hence predict the best consumption profile for that population given their battery properties and individual load profiles. Our framework also allows us to compute theoretical bounds on the amount of storage that will be adopted by the population. Second, to analyse the practical implications of micro-storage deployments in the grid, we present a novel algorithm that each agent can use to optimise its battery storage profile in order to minimise its owner's costs. This algorithm uses a learning strategy that allows it to adapt as the price of electricity changes in real-time, and we show that the adoption of these strategies results in the system converging to the theoretical equilibria. Finally, we empirically evaluate the adoption of our micro-storage management technique within a complex setting, based on the UK electricity market, where agents may have widely varying load profiles, battery types, and learning rates. In this case, our approach yields savings of up to 14% in energy cost for an average consumer using a storage device with a capacity of less than 4.5 kWh and up to a 7% reduction in carbon emissions resulting from electricity generation (with only domestic consumers adopting micro-storage and, commercial and industrial consumers not changing their demand). Moreover, corroborating our theoretical bound, an equilibrium is shown to exist where no more than 48% of households would wish to own storage devices and where social welfare would also be improved (yielding overall annual savings of nearly pounds1.5B).},
note = {AAMAS 2010 iRobot Best Paper Award},
keywords = {agents, Energy, mas, multi-agent systems, provenance},
pubstate = {published},
tppubtype = {article}
}
In this paper, we present a novel decentralised management technique that allows electricity micro-storage devices, deployed within individual homes as part of a smart electricity grid, to converge to profitable and efficient behaviours. Specifically, we propose the use of software agents, residing on the users' smart meters, to automate and optimise the charging cycle of micro-storage devices in the home to minimise its costs, and we present a study of both the theoretical underpinnings and the implications of a practical solution, of using software agents for such micro-storage management. First, by formalising the strategic choice each agent makes in deciding when to charge its battery, we develop a game-theoretic framework within which we can analyse the competitive equilibria of an electricity grid populated by such agents and hence predict the best consumption profile for that population given their battery properties and individual load profiles. Our framework also allows us to compute theoretical bounds on the amount of storage that will be adopted by the population. Second, to analyse the practical implications of micro-storage deployments in the grid, we present a novel algorithm that each agent can use to optimise its battery storage profile in order to minimise its owner's costs. This algorithm uses a learning strategy that allows it to adapt as the price of electricity changes in real-time, and we show that the adoption of these strategies results in the system converging to the theoretical equilibria. Finally, we empirically evaluate the adoption of our micro-storage management technique within a complex setting, based on the UK electricity market, where agents may have widely varying load profiles, battery types, and learning rates. In this case, our approach yields savings of up to 14% in energy cost for an average consumer using a storage device with a capacity of less than 4.5 kWh and up to a 7% reduction in carbon emissions resulting from electricity generation (with only domestic consumers adopting micro-storage and, commercial and industrial consumers not changing their demand). Moreover, corroborating our theoretical bound, an equilibrium is shown to exist where no more than 48% of households would wish to own storage devices and where social welfare would also be improved (yielding overall annual savings of nearly pounds1.5B).
2010
Macarthur, Kathryn; Farinelli, Alessandro; Ramchurn, Sarvapali; Jennings, Nick
Efficient, Superstabilizing Decentralised Optimisation for Dynamic Task Allocation Environments Proceedings Article
In: Third International Workshop on: Optimisation in Multi-Agent Systems (OptMas) at the Ninth Joint Conference on Autonomous and Multi-Agent Systems, pp. 25–32, 2010, (Event Dates: 10 May 2010).
Abstract | Links | BibTeX | Tags: agents, Disaster Management, mas, Multi-agent scheduling, multi-agent systems
@inproceedings{eps268588,
title = {Efficient, Superstabilizing Decentralised Optimisation for Dynamic Task Allocation Environments},
author = {Kathryn Macarthur and Alessandro Farinelli and Sarvapali Ramchurn and Nick Jennings},
url = {http://eprints.soton.ac.uk/268588/},
year = {2010},
date = {2010-01-01},
booktitle = {Third International Workshop on: Optimisation in Multi-Agent Systems (OptMas) at the Ninth Joint Conference on Autonomous and Multi-Agent Systems},
pages = {25–32},
abstract = {Decentralised optimisation is a key issue for multi-agent systems, and while many solution techniques have been developed, few provide support for dynamic environments, which change over time, such as disaster management. Given this, in this paper, we present Bounded Fast Max Sum (BFMS): a novel, dynamic, superstabilizing algorithm which provides a bounded approximate solution to certain classes of distributed constraint optimisation problems. We achieve this by eliminating dependencies in the constraint functions, according to how much impact they have on the overall solution value. In more detail, we propose iGHS, which computes a maximum spanning tree on subsections of the constraint graph, in order to reduce communication and computation overheads. Given this, we empirically evaluate BFMS, which shows that BFMS reduces communication and computation done by Bounded Max Sum by up to 99%, while obtaining 60-88% of the optimal utility.},
note = {Event Dates: 10 May 2010},
keywords = {agents, Disaster Management, mas, Multi-agent scheduling, multi-agent systems},
pubstate = {published},
tppubtype = {inproceedings}
}
Decentralised optimisation is a key issue for multi-agent systems, and while many solution techniques have been developed, few provide support for dynamic environments, which change over time, such as disaster management. Given this, in this paper, we present Bounded Fast Max Sum (BFMS): a novel, dynamic, superstabilizing algorithm which provides a bounded approximate solution to certain classes of distributed constraint optimisation problems. We achieve this by eliminating dependencies in the constraint functions, according to how much impact they have on the overall solution value. In more detail, we propose iGHS, which computes a maximum spanning tree on subsections of the constraint graph, in order to reduce communication and computation overheads. Given this, we empirically evaluate BFMS, which shows that BFMS reduces communication and computation done by Bounded Max Sum by up to 99%, while obtaining 60-88% of the optimal utility.
Ramchurn, S. D.; Polukarov, Mariya; Farinelli, Alessandro; Jennings, Nick; Trong, Cuong
Coalition Formation with Spatial and Temporal Constraints Proceedings Article
In: International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2010), pp. 1181–1188, 2010, (Event Dates: May 2010).
Abstract | Links | BibTeX | Tags: agents, Coalition Formation, Disaster Management, Multi-agent scheduling, RoboCup Rescue
@inproceedings{eps268497,
title = {Coalition Formation with Spatial and Temporal Constraints},
author = {S. D. Ramchurn and Mariya Polukarov and Alessandro Farinelli and Nick Jennings and Cuong Trong},
url = {http://eprints.soton.ac.uk/268497/},
year = {2010},
date = {2010-01-01},
booktitle = {International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2010)},
pages = {1181–1188},
abstract = {The coordination of emergency responders and robots to undertake a number of tasks in disaster scenarios is a grand challenge for multi-agent systems. Central to this endeavour is the problem of forming the best teams (coalitions) of responders to perform the various tasks in the area where the disaster has struck. Moreover, these teams may have to form, disband, and reform in different areas of the disaster region. This is because in most cases there will be more tasks than agents. Hence, agents need to schedule themselves to attempt each task in turn. Second, the tasks themselves can be very complex: requiring the agents to work on them for different lengths of time and having deadlines by when they need to be completed. The problem is complicated still further when different coalitions perform tasks with different levels of efficiency. Given all these facets, we define this as The Coalition Formation with Spatial and Temporal constraints problem (CFSTP).We show that this problem is NP-hard–in particular, it contains the wellknown complex combinatorial problem of Team Orienteering as a special case. Based on this, we design a Mixed Integer Program to optimally solve small-scale instances of the CFSTP and develop new anytime heuristics that can, on average, complete 97% of the tasks for large problems (20 agents and 300 tasks). In so doing, our solutions represent the first results for CFSTP.},
note = {Event Dates: May 2010},
keywords = {agents, Coalition Formation, Disaster Management, Multi-agent scheduling, RoboCup Rescue},
pubstate = {published},
tppubtype = {inproceedings}
}
The coordination of emergency responders and robots to undertake a number of tasks in disaster scenarios is a grand challenge for multi-agent systems. Central to this endeavour is the problem of forming the best teams (coalitions) of responders to perform the various tasks in the area where the disaster has struck. Moreover, these teams may have to form, disband, and reform in different areas of the disaster region. This is because in most cases there will be more tasks than agents. Hence, agents need to schedule themselves to attempt each task in turn. Second, the tasks themselves can be very complex: requiring the agents to work on them for different lengths of time and having deadlines by when they need to be completed. The problem is complicated still further when different coalitions perform tasks with different levels of efficiency. Given all these facets, we define this as The Coalition Formation with Spatial and Temporal constraints problem (CFSTP).We show that this problem is NP-hard–in particular, it contains the wellknown complex combinatorial problem of Team Orienteering as a special case. Based on this, we design a Mixed Integer Program to optimally solve small-scale instances of the CFSTP and develop new anytime heuristics that can, on average, complete 97% of the tasks for large problems (20 agents and 300 tasks). In so doing, our solutions represent the first results for CFSTP.
Ramchurn, Sarvapali; Farinelli, Alessandro; Macarthur, Kathryn; Polukarov, Mariya; Jennings, Nick
Decentralised Coordination in RoboCup Rescue Journal Article
In: The Computer Journal, vol. 53, no. 9, pp. 1–15, 2010.
Abstract | Links | BibTeX | Tags: Disaster Management, mas, Multi-agent scheduling, multi-agent systems
@article{eps268499,
title = {Decentralised Coordination in RoboCup Rescue},
author = {Sarvapali Ramchurn and Alessandro Farinelli and Kathryn Macarthur and Mariya Polukarov and Nick Jennings},
url = {http://eprints.soton.ac.uk/268499/},
year = {2010},
date = {2010-01-01},
journal = {The Computer Journal},
volume = {53},
number = {9},
pages = {1–15},
publisher = {Oxford Journals},
abstract = {Emergency responders are faced with a number of significant challenges when managing major disasters. First, the number of rescue tasks posed is usually larger than the number of responders (or agents) and the resources available to them. Second, each task is likely to require a different level of effort in order to be completed by its deadline. Third, new tasks may continually appear or disappear from the environment, thus requiring the responders to quickly recompute their allocation of resources. Fourth, forming teams or coalitions of multiple agents from different agencies is vital since no single agency will have all the resources needed to save victims, unblock roads, and extinguish the ?res which might erupt in the disaster space. Given this, coalitions have to be efficiently selected and scheduled to work across the disaster space so as to maximise the number of lives and the portion of the infrastructure saved. In particular, it is important that the selection of such coalitions should be performed in a decentralised fashion in order to avoid a single point of failure in the system. Moreover, it is critical that responders communicate only locally given they are likely to have limited battery power or minimal access to long range communication devices. Against this background, we provide a novel decentralised solution to the coalition formation process that pervades disaster management. More specifically, we model the emergency management scenario defined in the RoboCup Rescue disaster simulation platform as a Coalition Formation with Spatial and Temporal constraints (CFST) problem where agents form coalitions in order to complete tasks, each with different demands. In order to design a decentralised algorithm for CFST we formulate it as a Distributed Constraint Optimisation problem and show how to solve it using the state-of-the-art Max-Sum algorithm that provides a completely decentralised message-passing solution. We then provide a novel algorithm (F-Max-Sum) that avoids sending redundant messages and efficiently adapts to changes in the environment. In empirical evaluations, our algorithm is shown to generate better solutions than other decentralised algorithms used for this problem.},
keywords = {Disaster Management, mas, Multi-agent scheduling, multi-agent systems},
pubstate = {published},
tppubtype = {article}
}
Emergency responders are faced with a number of significant challenges when managing major disasters. First, the number of rescue tasks posed is usually larger than the number of responders (or agents) and the resources available to them. Second, each task is likely to require a different level of effort in order to be completed by its deadline. Third, new tasks may continually appear or disappear from the environment, thus requiring the responders to quickly recompute their allocation of resources. Fourth, forming teams or coalitions of multiple agents from different agencies is vital since no single agency will have all the resources needed to save victims, unblock roads, and extinguish the ?res which might erupt in the disaster space. Given this, coalitions have to be efficiently selected and scheduled to work across the disaster space so as to maximise the number of lives and the portion of the infrastructure saved. In particular, it is important that the selection of such coalitions should be performed in a decentralised fashion in order to avoid a single point of failure in the system. Moreover, it is critical that responders communicate only locally given they are likely to have limited battery power or minimal access to long range communication devices. Against this background, we provide a novel decentralised solution to the coalition formation process that pervades disaster management. More specifically, we model the emergency management scenario defined in the RoboCup Rescue disaster simulation platform as a Coalition Formation with Spatial and Temporal constraints (CFST) problem where agents form coalitions in order to complete tasks, each with different demands. In order to design a decentralised algorithm for CFST we formulate it as a Distributed Constraint Optimisation problem and show how to solve it using the state-of-the-art Max-Sum algorithm that provides a completely decentralised message-passing solution. We then provide a novel algorithm (F-Max-Sum) that avoids sending redundant messages and efficiently adapts to changes in the environment. In empirical evaluations, our algorithm is shown to generate better solutions than other decentralised algorithms used for this problem.
Vytelingum, Perukrishnen; Ramchurn, Sarvapali D.; Voice, Thomas D.; Rogers, Alex; Jennings, Nicholas R.
Trading agents for the smart electricity grid Proceedings Article
In: The Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), pp. 897–904, 2010, (Event Dates: May 10-14, 2010).
Abstract | Links | BibTeX | Tags: agents, balancing mechanism, continuous double auction, Energy, markets, smart grid
@inproceedings{eps268361,
title = {Trading agents for the smart electricity grid},
author = {Perukrishnen Vytelingum and Sarvapali D. Ramchurn and Thomas D. Voice and Alex Rogers and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/268361/},
year = {2010},
date = {2010-01-01},
booktitle = {The Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010)},
pages = {897–904},
abstract = {The vision of the Smart Grid includes the creation of intelligent electricity supply networks to allow efficient use of energy resources, reduce carbon emissions and are robust to failures. One of the key assumptions underlying this vision is that it will be possible to manage the trading of electricity between homes and micro-grids while coping with the inherent real-time dynamism in electricity demand and supply. The management of these trades needs to take into account the fact that most, if not all, of the actors in the system are self-interested and transmission line capacities are constrained. Against this background, we develop and evaluate a novel market-based mechanism and novel trading strategies for the Smart Grid. Our mechanism is based on the Continuous Double Auction (CDA) and automatically manages the congestion within the system by pricing the flow of electricity. We also introduce mechanisms to ensure the system can cope with unforeseen demand or increased supply capacity in real time. Finally, we develop new strategies that we show achieve high market efficiency (typically over 90%).},
note = {Event Dates: May 10-14, 2010},
keywords = {agents, balancing mechanism, continuous double auction, Energy, markets, smart grid},
pubstate = {published},
tppubtype = {inproceedings}
}
The vision of the Smart Grid includes the creation of intelligent electricity supply networks to allow efficient use of energy resources, reduce carbon emissions and are robust to failures. One of the key assumptions underlying this vision is that it will be possible to manage the trading of electricity between homes and micro-grids while coping with the inherent real-time dynamism in electricity demand and supply. The management of these trades needs to take into account the fact that most, if not all, of the actors in the system are self-interested and transmission line capacities are constrained. Against this background, we develop and evaluate a novel market-based mechanism and novel trading strategies for the Smart Grid. Our mechanism is based on the Continuous Double Auction (CDA) and automatically manages the congestion within the system by pricing the flow of electricity. We also introduce mechanisms to ensure the system can cope with unforeseen demand or increased supply capacity in real time. Finally, we develop new strategies that we show achieve high market efficiency (typically over 90%).
Vytelingum, Perukrishnen; Voice, Thomas D.; Ramchurn, Sarvapali D.; Rogers, Alex; Jennings, Nicholas R.
Agent-Based Micro-Storage Management for the Smart Grid Proceedings Article
In: The Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010) - Won the Best Paper Award, pp. 39–46, 2010, (Winner of the Best Paper Award Event Dates: May 10-14, 2010).
Abstract | Links | BibTeX | Tags: agent-based modelling, agents, Energy, game-theory, smart grid
@inproceedings{eps268360,
title = {Agent-Based Micro-Storage Management for the Smart Grid},
author = {Perukrishnen Vytelingum and Thomas D. Voice and Sarvapali D. Ramchurn and Alex Rogers and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/268360/},
year = {2010},
date = {2010-01-01},
booktitle = {The Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010) - Won the Best Paper Award},
pages = {39–46},
abstract = {The use of energy storage devices in homes has been advocated as one of the main ways of saving energy and reducing the reliance on fossil fuels in the future Smart Grid. However, if micro-storage devices are all charged at the same time using power from the electricity grid, it means a higher demand and, hence, more generation capacity, more carbon emissions, and, in the worst case, breaking down the system due to over-demand. To alleviate such issues, in this paper, we present a novel agent-based micro-storage management technique that allows all (individually-owned) storage devices in the system to converge to profitable, efficient behaviour. Specifically, we provide a general framework within which to analyse the Nash equilibrium of an electricity grid and devise new agent-based storage learning strategies that adapt to market conditions. Taken altogether, our solution shows that, specifically, in the UK electricity market, it is possible to achieve savings of up to 13% on average for a consumer on his electricity bill with a storage device of 4 kWh. Moreover, we show that there exists an equilibrium where only 38% of UK households would own storage devices and where social welfare would be also maximised (with an overall annual savings of nearly GBP 1.5B at that equilibrium).},
note = {Winner of the Best Paper Award Event Dates: May 10-14, 2010},
keywords = {agent-based modelling, agents, Energy, game-theory, smart grid},
pubstate = {published},
tppubtype = {inproceedings}
}
The use of energy storage devices in homes has been advocated as one of the main ways of saving energy and reducing the reliance on fossil fuels in the future Smart Grid. However, if micro-storage devices are all charged at the same time using power from the electricity grid, it means a higher demand and, hence, more generation capacity, more carbon emissions, and, in the worst case, breaking down the system due to over-demand. To alleviate such issues, in this paper, we present a novel agent-based micro-storage management technique that allows all (individually-owned) storage devices in the system to converge to profitable, efficient behaviour. Specifically, we provide a general framework within which to analyse the Nash equilibrium of an electricity grid and devise new agent-based storage learning strategies that adapt to market conditions. Taken altogether, our solution shows that, specifically, in the UK electricity market, it is possible to achieve savings of up to 13% on average for a consumer on his electricity bill with a storage device of 4 kWh. Moreover, we show that there exists an equilibrium where only 38% of UK households would own storage devices and where social welfare would be also maximised (with an overall annual savings of nearly GBP 1.5B at that equilibrium).
2009
Rahwan, Talal; Ramchurn, Sarvapali; Jennings, Nicholas; Giovannucci, Andrea
An anytime algorithm for optimal coalition structure generation Journal Article
In: Journal of Artificial Intelligence Research, vol. 34, pp. 521–567, 2009.
Abstract | Links | BibTeX | Tags: Coalition Formation, multi-agent systems
@article{eps267179,
title = {An anytime algorithm for optimal coalition structure generation},
author = {Talal Rahwan and Sarvapali Ramchurn and Nicholas Jennings and Andrea Giovannucci},
url = {http://eprints.soton.ac.uk/267179/},
year = {2009},
date = {2009-01-01},
journal = {Journal of Artificial Intelligence Research},
volume = {34},
pages = {521–567},
abstract = {Coalition formation is a fundamental type of interaction that involves the creation of coherent groupings of distinct, autonomous, agents in order to efficiently achieve their individual or collective goals. Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining which of the many possible coalitions to form in order to achieve some goal. This usually requires calculating a value for every possible coalition, known as the coalition value, which indicates how beneficial that coalition would be if it was formed. Once these values are calculated, the agents usually need to find a combination of coalitions, in which every agent belongs to exactly one coalition, and by which the overall outcome of the system is maximized. However, this coalition structure generation problem is extremely challenging due to the number of possible solutions that need to be examined, which grows exponentially with the number of agents involved. To date, therefore, many algorithms have been proposed to solve this problem using different techniques–ranging from dynamic programming, to integer programming, to stochastic search – all of which suffer from major limitations relating to execution time, solution quality, and memory requirements. With this in mind, we develop an anytime algorithm to solve the coalition structure generation problem. Specifically, the algorithm uses a novel representation of the search space, which partitions the space of possible solutions into sub-spaces such that it is possible to compute upper and lower bounds on the values of the best coalition structures in them. These bounds are then used to identify the sub-spaces that have no potential of containing the optimal solution so that they can be pruned. The algorithm, then, searches through the remaining sub-spaces very efficiently using a branch-and-bound technique to avoid examining all the solutions within the searched subspace(s). In this setting, we prove that our algorithm enumerates all coalition structures efficiently by avoiding redundant and invalid solutions automatically. Moreover, in order to effectively test our algorithm we develop a new type of input distribution which allows us to generate more reliable benchmarks compared to the input distributions previously used in the field. Given this new distribution, we show that for 27 agents our algorithm is able to find solutions that are optimal in 0:175% of the time required by the fastest available algorithm in the literature. The algorithm is anytime, and if interrupted before it would have normally terminated, it can still provide a solution that is guaranteed to be within a bound from the optimal one. Moreover, the guarantees we provide on the quality of the solution are significantly better than those provided by the previous state of the art algorithms designed for this purpose. For example, for the worst case distribution given 25 agents, our algorithm is able to find a 90% efficient solution in around 10% of time it takes to find the optimal solution.},
keywords = {Coalition Formation, multi-agent systems},
pubstate = {published},
tppubtype = {article}
}
Coalition formation is a fundamental type of interaction that involves the creation of coherent groupings of distinct, autonomous, agents in order to efficiently achieve their individual or collective goals. Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining which of the many possible coalitions to form in order to achieve some goal. This usually requires calculating a value for every possible coalition, known as the coalition value, which indicates how beneficial that coalition would be if it was formed. Once these values are calculated, the agents usually need to find a combination of coalitions, in which every agent belongs to exactly one coalition, and by which the overall outcome of the system is maximized. However, this coalition structure generation problem is extremely challenging due to the number of possible solutions that need to be examined, which grows exponentially with the number of agents involved. To date, therefore, many algorithms have been proposed to solve this problem using different techniques–ranging from dynamic programming, to integer programming, to stochastic search – all of which suffer from major limitations relating to execution time, solution quality, and memory requirements. With this in mind, we develop an anytime algorithm to solve the coalition structure generation problem. Specifically, the algorithm uses a novel representation of the search space, which partitions the space of possible solutions into sub-spaces such that it is possible to compute upper and lower bounds on the values of the best coalition structures in them. These bounds are then used to identify the sub-spaces that have no potential of containing the optimal solution so that they can be pruned. The algorithm, then, searches through the remaining sub-spaces very efficiently using a branch-and-bound technique to avoid examining all the solutions within the searched subspace(s). In this setting, we prove that our algorithm enumerates all coalition structures efficiently by avoiding redundant and invalid solutions automatically. Moreover, in order to effectively test our algorithm we develop a new type of input distribution which allows us to generate more reliable benchmarks compared to the input distributions previously used in the field. Given this new distribution, we show that for 27 agents our algorithm is able to find solutions that are optimal in 0:175% of the time required by the fastest available algorithm in the literature. The algorithm is anytime, and if interrupted before it would have normally terminated, it can still provide a solution that is guaranteed to be within a bound from the optimal one. Moreover, the guarantees we provide on the quality of the solution are significantly better than those provided by the previous state of the art algorithms designed for this purpose. For example, for the worst case distribution given 25 agents, our algorithm is able to find a 90% efficient solution in around 10% of time it takes to find the optimal solution.
Ramchurn, Sarvapali D.; Mezzetti, Claudio; Giovannucci, Andrea; Rodriguez, Juan A.; Dash, Rajdeep K.; Jennings, Nicholas R.
Trust-based mechanisms for robust and efficient task allocation in the presence of execution uncertainty Journal Article
In: Journal of Artificial Intelligence Research, vol. 35, pp. 1–41, 2009.
Abstract | Links | BibTeX | Tags: mechanism design, optimisation, Trust, uncertainty
@article{eps267288,
title = {Trust-based mechanisms for robust and efficient task allocation in the presence of execution uncertainty},
author = {Sarvapali D. Ramchurn and Claudio Mezzetti and Andrea Giovannucci and Juan A. Rodriguez and Rajdeep K. Dash and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/267288/},
year = {2009},
date = {2009-01-01},
journal = {Journal of Artificial Intelligence Research},
volume = {35},
pages = {1–41},
abstract = {Vickrey-Clarke-Groves (VCG) mechanisms are often used to allocate tasks to selfish and rational agents. VCG mechanisms are incentive-compatible, direct mechanisms that are efficient (i.e. maximise social utility) and individually rational (i.e. agents prefer to join rather than opt out). However, an important assumption of these mechanisms is that the agents will always successfully complete their allocated tasks. Clearly, this assumption is unrealistic in many real-world applications where agents can, and often do, fail in their endeavours. Moreover, whether an agent is deemed to have failed may be perceived differently by different agents. Such subjective perceptions about an agent's probability of succeeding at a given task are often captured and reasoned about using the notion of trust. Given this background, in this paper we investigate the design of novel mechanisms that take into account the trust between agents when allocating tasks. Specifically, we develop a new class of mechanisms, called trust-based mechanisms, that can take into account multiple subjective measures of the probability of an agent succeeding at a given task and produce allocations that maximise social utility, whilst ensuring that no agent obtains a negative utility. We then show that such mechanisms pose a challenging new combinatorial optimisation problem (that is NP-complete), devise a novel representation for solving the problem, and develop an effective integer programming solution (that can solve instances with about 2x10^ 5 possible allocations in 40 seconds).},
keywords = {mechanism design, optimisation, Trust, uncertainty},
pubstate = {published},
tppubtype = {article}
}
Vickrey-Clarke-Groves (VCG) mechanisms are often used to allocate tasks to selfish and rational agents. VCG mechanisms are incentive-compatible, direct mechanisms that are efficient (i.e. maximise social utility) and individually rational (i.e. agents prefer to join rather than opt out). However, an important assumption of these mechanisms is that the agents will always successfully complete their allocated tasks. Clearly, this assumption is unrealistic in many real-world applications where agents can, and often do, fail in their endeavours. Moreover, whether an agent is deemed to have failed may be perceived differently by different agents. Such subjective perceptions about an agent's probability of succeeding at a given task are often captured and reasoned about using the notion of trust. Given this background, in this paper we investigate the design of novel mechanisms that take into account the trust between agents when allocating tasks. Specifically, we develop a new class of mechanisms, called trust-based mechanisms, that can take into account multiple subjective measures of the probability of an agent succeeding at a given task and produce allocations that maximise social utility, whilst ensuring that no agent obtains a negative utility. We then show that such mechanisms pose a challenging new combinatorial optimisation problem (that is NP-complete), devise a novel representation for solving the problem, and develop an effective integer programming solution (that can solve instances with about 2x10^ 5 possible allocations in 40 seconds).
Valkenhoef, Gert; Ramchurn, Sarvapali D.; Vytelingum, Perukrishnen; Jennings, Nicholas R.; Verbrugge, Rinek
Continuous double auctions with execution uncertainty Proceedings Article
In: Workshop on Trading Agent Design and Analysis (TADA-09), 2009.
Abstract | Links | BibTeX | Tags:
@inproceedings{eps267329,
title = {Continuous double auctions with execution uncertainty},
author = {Gert Valkenhoef and Sarvapali D. Ramchurn and Perukrishnen Vytelingum and Nicholas R. Jennings and Rinek Verbrugge},
url = {http://eprints.soton.ac.uk/267329/},
year = {2009},
date = {2009-01-01},
booktitle = {Workshop on Trading Agent Design and Analysis (TADA-09)},
abstract = {We propose a novel variant of the Continuous Double Auction (CDA), the Trust-based CDA (T-CDA), which we demonstrate to be robust to execution uncertainty. This is desirable in a setting where traders may fail to deliver the goods, services or payments they have promised. Specifically, the TCDA provides a mechanism that allows agents to commit to trades they believe will maximize their expected utility. In this paper, we consider agents that use their trust in other agents to estimate the expected utility of a transaction. We empirically evaluate the mechanism, both against the optimal solution given perfect and complete information and against the standard CDA.We show that the T-CDA consistently outperforms the traditional CDA as execution uncertainty increases in the system. Furthermore, we investigate the robustness of the mechanism to unreliable trust information and find that performance degrades gracefully as information quality decreases.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We propose a novel variant of the Continuous Double Auction (CDA), the Trust-based CDA (T-CDA), which we demonstrate to be robust to execution uncertainty. This is desirable in a setting where traders may fail to deliver the goods, services or payments they have promised. Specifically, the TCDA provides a mechanism that allows agents to commit to trades they believe will maximize their expected utility. In this paper, we consider agents that use their trust in other agents to estimate the expected utility of a transaction. We empirically evaluate the mechanism, both against the optimal solution given perfect and complete information and against the standard CDA.We show that the T-CDA consistently outperforms the traditional CDA as execution uncertainty increases in the system. Furthermore, we investigate the robustness of the mechanism to unreliable trust information and find that performance degrades gracefully as information quality decreases.
2008
Adams, Niall; Field, Martin; Gelenbe, Erol; Hand, David; Jennings, Nicholas; Leslie, David; Nicholson, David; Ramchurn, Sarvapali; Rogers, Alex
Intelligent Agents for Disaster Management Proceedings Article
In: Proceedings of the IARP/EURON Workshop on Robotics for Risky Interventions and Environmental Surveillance (RISE), 2008.
Abstract | Links | BibTeX | Tags:
@inproceedings{eps272011,
title = {Intelligent Agents for Disaster Management},
author = {Niall Adams and Martin Field and Erol Gelenbe and David Hand and Nicholas Jennings and David Leslie and David Nicholson and Sarvapali Ramchurn and Alex Rogers},
url = {http://eprints.soton.ac.uk/272011/},
year = {2008},
date = {2008-01-01},
booktitle = {Proceedings of the IARP/EURON Workshop on Robotics for Risky Interventions and Environmental Surveillance (RISE)},
abstract = {ALADDIN [1] is a multi-disciplinary project that is developing novel techniques, architectures, and mechanisms for multi-agent systems in uncertain and dynamic environments. The application focus of the project is disaster management. Research within a number of themes is being pursued and this is considering different aspects of the interaction between autonomous agents and the decentralised system architectures that support those interactions. The aim of the research is to contribute to building more robust multi-agent systems for future applications in disaster management and other similar domains.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
ALADDIN [1] is a multi-disciplinary project that is developing novel techniques, architectures, and mechanisms for multi-agent systems in uncertain and dynamic environments. The application focus of the project is disaster management. Research within a number of themes is being pursued and this is considering different aspects of the interaction between autonomous agents and the decentralised system architectures that support those interactions. The aim of the research is to contribute to building more robust multi-agent systems for future applications in disaster management and other similar domains.
Osborne, Michael A; Rogers, Alex; Ramchurn, Sarvapali; Roberts, Stephen J; Jennings, N. R.
Towards Real-Time Information Processing of Sensor Network Data using Computationally Efficient Multi-output Gaussian Processes Proceedings Article
In: International Conference on Information Processing in Sensor Networks (IPSN 2008), pp. 109–120, 2008, (Event Dates: April 2008).
Abstract | Links | BibTeX | Tags:
@inproceedings{eps265122,
title = {Towards Real-Time Information Processing of Sensor Network Data using Computationally Efficient Multi-output Gaussian Processes},
author = {Michael A Osborne and Alex Rogers and Sarvapali Ramchurn and Stephen J Roberts and N. R. Jennings},
url = {http://eprints.soton.ac.uk/265122/},
year = {2008},
date = {2008-01-01},
booktitle = {International Conference on Information Processing in Sensor Networks (IPSN 2008)},
pages = {109–120},
abstract = {In this paper, we describe a novel, computationally efficient algorithm that facilitates the autonomous acquisition of readings from sensor networks (deciding when and which sensor to acquire readings from at any time), and which can, with minimal domain knowledge, perform a range of information processing tasks including modelling the accuracy of the sensor readings, predicting the value of missing sensor readings, and predicting how the monitored environmental variables will evolve into the future. Our motivating scenario is the need to provide situational awareness support to first responders at the scene of a large scale incident, and to this end, we describe a novel iterative formulation of a multi-output Gaussian process that can build and exploit a probabilistic model of the environmental variables being measured (including the correlations and delays that exist between them). We validate our approach using data collected from a network of weather sensors located on the south coast of England.},
note = {Event Dates: April 2008},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, we describe a novel, computationally efficient algorithm that facilitates the autonomous acquisition of readings from sensor networks (deciding when and which sensor to acquire readings from at any time), and which can, with minimal domain knowledge, perform a range of information processing tasks including modelling the accuracy of the sensor readings, predicting the value of missing sensor readings, and predicting how the monitored environmental variables will evolve into the future. Our motivating scenario is the need to provide situational awareness support to first responders at the scene of a large scale incident, and to this end, we describe a novel iterative formulation of a multi-output Gaussian process that can build and exploit a probabilistic model of the environmental variables being measured (including the correlations and delays that exist between them). We validate our approach using data collected from a network of weather sensors located on the south coast of England.
Rogers, Alex; Osborne, Michael A; Ramchurn, Sarvapali; Roberts, Stephen J; Jennings, N. R.
Information Agents for Pervasive Sensor Networks Proceedings Article
In: Sixth Annual IEEE International Conference on Pervasive Computing and Communications (PerCom 2008), pp. 294–299, 2008, (Event Dates: March 2008).
Abstract | Links | BibTeX | Tags:
@inproceedings{eps264967,
title = {Information Agents for Pervasive Sensor Networks},
author = {Alex Rogers and Michael A Osborne and Sarvapali Ramchurn and Stephen J Roberts and N. R. Jennings},
url = {http://eprints.soton.ac.uk/264967/},
year = {2008},
date = {2008-01-01},
booktitle = {Sixth Annual IEEE International Conference on Pervasive Computing and Communications (PerCom 2008)},
pages = {294–299},
abstract = {In this paper, we describe an information agent, that resides on a mobile computer or personal digital assistant (PDA), that can autonomously acquire sensor readings from pervasive sensor networks (deciding when and which sensor to acquire readings from at any time). Moreover, it can perform a range of information processing tasks including modelling the accuracy of the sensor readings, predicting the value of missing sensor readings, and predicting how the monitored environmental parameters will evolve into the future. Our motivating scenario is the need to provide situational awareness support to first responders at the scene of a large scale incident, and we describe how we use an iterative formulation of a multi-output Gaussian process to build a probabilistic model of the environmental parameters being measured by local sensors, and the correlations and delays that exist between them. We validate our approach using data collected from a network of weather sensors located on the south coast of England.},
note = {Event Dates: March 2008},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, we describe an information agent, that resides on a mobile computer or personal digital assistant (PDA), that can autonomously acquire sensor readings from pervasive sensor networks (deciding when and which sensor to acquire readings from at any time). Moreover, it can perform a range of information processing tasks including modelling the accuracy of the sensor readings, predicting the value of missing sensor readings, and predicting how the monitored environmental parameters will evolve into the future. Our motivating scenario is the need to provide situational awareness support to first responders at the scene of a large scale incident, and we describe how we use an iterative formulation of a multi-output Gaussian process to build a probabilistic model of the environmental parameters being measured by local sensors, and the correlations and delays that exist between them. We validate our approach using data collected from a network of weather sensors located on the south coast of England.
2007
Espinoza, Fredrik; Roure, David De; Hamfors, Ola; Hinz, Lucas; Holmberg, Jesper; Jansson, Carl-Gustaf; Jennings, Nick; Luck, Mike; L"onnqvist, Peter; Ramchurn, Sarvapali; Sandin, Anna; Thompson, Mark; Bylund, Markus
Intrusiveness Management for Focused, Efficient, and Enjoyable Activities Book Section
In: The Disappearing Computer: Interaction Design, System Infrastructures and Applications for Smart Environments, pp. 143–160, Springer, 2007.
@incollection{eps265985,
title = {Intrusiveness Management for Focused, Efficient, and Enjoyable Activities},
author = {Fredrik Espinoza and David De Roure and Ola Hamfors and Lucas Hinz and Jesper Holmberg and Carl-Gustaf Jansson and Nick Jennings and Mike Luck and Peter L"onnqvist and Sarvapali Ramchurn and Anna Sandin and Mark Thompson and Markus Bylund},
url = {http://eprints.soton.ac.uk/265985/},
year = {2007},
date = {2007-01-01},
booktitle = {The Disappearing Computer: Interaction Design, System Infrastructures and Applications for Smart Environments},
pages = {143–160},
publisher = {Springer},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
Rahwan, T.; Ramchurn, S. D.; Dang, V. D.; Jennings, N. R.
Near-optimal anytime coalition structure generation Proceedings Article
In: 20th International Joint Conference on Artificial Intelligence (IJCAI), pp. 2365–2371, 2007.
Abstract | Links | BibTeX | Tags:
@inproceedings{eps263074,
title = {Near-optimal anytime coalition structure generation},
author = {T. Rahwan and S. D. Ramchurn and V. D. Dang and N. R. Jennings},
url = {http://eprints.soton.ac.uk/263074/},
year = {2007},
date = {2007-01-01},
booktitle = {20th International Joint Conference on Artificial Intelligence (IJCAI)},
pages = {2365–2371},
abstract = {Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best set of agents that should participate in a given team. To this end, in this paper, we present a novel, anytime algorithms designed for this purpose. Our algorithm can generate solutions that either have a tight bound from the optimal or are optimal (depending on the objective) and works by partitioning the space in terms of a small set of elements that represent structures which contain coalitions of particular sizes. It then performs an online heuristic search that prunes the space and only considers valid and non-redundant coalition structures. We empirically show that we are able to find solutions that are, in the worst case, 99% efficient in 0.0043% of the time to find the optimal value by the state of the art dynamic programming (DP) algorithm (for 20 agents), using 33% less memory.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best set of agents that should participate in a given team. To this end, in this paper, we present a novel, anytime algorithms designed for this purpose. Our algorithm can generate solutions that either have a tight bound from the optimal or are optimal (depending on the objective) and works by partitioning the space in terms of a small set of elements that represent structures which contain coalitions of particular sizes. It then performs an online heuristic search that prunes the space and only considers valid and non-redundant coalition structures. We empirically show that we are able to find solutions that are, in the worst case, 99% efficient in 0.0043% of the time to find the optimal value by the state of the art dynamic programming (DP) algorithm (for 20 agents), using 33% less memory.
Rahwan, Talal; Ramchurn, Sarvapali D.; Dang, Viet D.; Giovannucci, Andrea; Jennings, N. R.
Anytime Optimal Coalition Structure Generation Proceedings Article
In: 22nd Conference on Artificial Intelligence (AAAI), pp. 1184–1190, 2007.
Abstract | Links | BibTeX | Tags: Coalition Formation, Coalition Structure Generation, Combinatorial, multi-agent systems, Search, Set Partitioning
@inproceedings{eps263433,
title = {Anytime Optimal Coalition Structure Generation},
author = {Talal Rahwan and Sarvapali D. Ramchurn and Viet D. Dang and Andrea Giovannucci and N. R. Jennings},
url = {http://eprints.soton.ac.uk/263433/},
year = {2007},
date = {2007-01-01},
booktitle = {22nd Conference on Artificial Intelligence (AAAI)},
pages = {1184–1190},
abstract = {Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best groups of agents to select to achieve some goal. To this end, in this paper, we present a novel, optimal anytime algorithm for this coalition structure generation problem that is significantly faster than previous algorithms designed for this purpose. Specifically, our algorithm can generate solutions by partitioning the space of all potential coalitions into sub-spaces that contain coalition structures that are similar, according to some criterion, such that these sub-spaces can be pruned by identifying their bounds. Using this representation, the algorithm then searches through only valid and unique coalition structures and selects the best among them using a branch-and-bound technique. We empirically show that we are able to find solutions that are optimal in 0.082% of the time taken by the state of the art dynamic programming algorithm (for 27 agents) using much less memory (O(2^ n) instead of O(3^ n) for the set of n agents). Moreover, our algorithm is the first to be able to solve the coalition structure generation problem for numbers of agents bigger than 27 in reasonable time (less than 90 minutes for 27 agents as opposed to around 2 months for the best previous solution).},
keywords = {Coalition Formation, Coalition Structure Generation, Combinatorial, multi-agent systems, Search, Set Partitioning},
pubstate = {published},
tppubtype = {inproceedings}
}
Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best groups of agents to select to achieve some goal. To this end, in this paper, we present a novel, optimal anytime algorithm for this coalition structure generation problem that is significantly faster than previous algorithms designed for this purpose. Specifically, our algorithm can generate solutions by partitioning the space of all potential coalitions into sub-spaces that contain coalition structures that are similar, according to some criterion, such that these sub-spaces can be pruned by identifying their bounds. Using this representation, the algorithm then searches through only valid and unique coalition structures and selects the best among them using a branch-and-bound technique. We empirically show that we are able to find solutions that are optimal in 0.082% of the time taken by the state of the art dynamic programming algorithm (for 27 agents) using much less memory (O(2^ n) instead of O(3^ n) for the set of n agents). Moreover, our algorithm is the first to be able to solve the coalition structure generation problem for numbers of agents bigger than 27 in reasonable time (less than 90 minutes for 27 agents as opposed to around 2 months for the best previous solution).
Ramchurn, S. D.; Sierra, C.; Godo, L.; Jennings, N. R.
Negotiating using rewards. Journal Article
In: Artificial Intelligence Journal., vol. 171, no. 10-15, pp. 805–837, 2007.
Abstract | Links | BibTeX | Tags: Bargaining, Bilateral Negotiation., Negotiation Tactics, Persuasive Negotiation, Repeated Negotiations
@article{eps264225,
title = {Negotiating using rewards.},
author = {S. D. Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/264225/},
year = {2007},
date = {2007-01-01},
journal = {Artificial Intelligence Journal.},
volume = {171},
number = {10-15},
pages = {805–837},
abstract = {Negotiation is a fundamental interaction mechanism in multi-agent systems because it allows self-interested agents to come to mutually beneficial agreements and partition resources efficiently and effectively. Now, in many situations, the agents need to negotiate with one another many times and so developing strategies that are effective over repeated interactions is an important challenge. Against this background, a growing body of work has examined the use of Persuasive Negotiation (PN), which involves negotiating using rhetorical arguments (such as threats, rewards, or appeals), in trying to convince an opponent to accept a given offer. Such mechanisms are especially suited to repeated encounters because they allow agents to influence the outcomes of future negotiations, while negotiating a deal in the present one, with the aim of producing results that are beneficial to both parties. To this end, in this paper, we develop a comprehensive PN mechanism for repeated interactions that makes use of rewards that can be asked for or given to. Our mechanism consists of two parts. First, a novel protocol that structures the interaction by capturing the commitments that agents incur when using rewards. Second, a new reward generation algorithm that constructs promises of rewards in future interactions as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. We then go on to develop a specific negotiation tactic, based on this reward generation algorithm, and show that it can achieve significantly better outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation in a Multi-Move Prisoners? dilemma setting, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this.},
keywords = {Bargaining, Bilateral Negotiation., Negotiation Tactics, Persuasive Negotiation, Repeated Negotiations},
pubstate = {published},
tppubtype = {article}
}
Negotiation is a fundamental interaction mechanism in multi-agent systems because it allows self-interested agents to come to mutually beneficial agreements and partition resources efficiently and effectively. Now, in many situations, the agents need to negotiate with one another many times and so developing strategies that are effective over repeated interactions is an important challenge. Against this background, a growing body of work has examined the use of Persuasive Negotiation (PN), which involves negotiating using rhetorical arguments (such as threats, rewards, or appeals), in trying to convince an opponent to accept a given offer. Such mechanisms are especially suited to repeated encounters because they allow agents to influence the outcomes of future negotiations, while negotiating a deal in the present one, with the aim of producing results that are beneficial to both parties. To this end, in this paper, we develop a comprehensive PN mechanism for repeated interactions that makes use of rewards that can be asked for or given to. Our mechanism consists of two parts. First, a novel protocol that structures the interaction by capturing the commitments that agents incur when using rewards. Second, a new reward generation algorithm that constructs promises of rewards in future interactions as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. We then go on to develop a specific negotiation tactic, based on this reward generation algorithm, and show that it can achieve significantly better outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation in a Multi-Move Prisoners? dilemma setting, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this.
Rogers, Alex; Dash, Rajdeep K.; Ramchurn, Sarvapali D.; Vytelingum, Perukrishnen; Jennings, N. R.
Coordinating Team Players within a Noisy Iterated Prisoner?s Dilemma Tournament Journal Article
In: Theoretical Computer Science, vol. 377, no. 1-3, pp. 243–259, 2007.
Abstract | Links | BibTeX | Tags:
@article{eps263238,
title = {Coordinating Team Players within a Noisy Iterated Prisoner?s Dilemma Tournament},
author = {Alex Rogers and Rajdeep K. Dash and Sarvapali D. Ramchurn and Perukrishnen Vytelingum and N. R. Jennings},
url = {http://eprints.soton.ac.uk/263238/},
year = {2007},
date = {2007-01-01},
journal = {Theoretical Computer Science},
volume = {377},
number = {1-3},
pages = {243–259},
abstract = {In this paper, we present our investigation into the use of a team of players within a noisy Iterated Prisoner?s Dilemma (IPD) tournament. We show that the members of such a team are able to use a pre-arranged sequence of moves that they make at the start of each interaction in order to recognise one another, and that by coordinating their actions they can increase the chances that one of the team members wins the round-robin style tournament. We consider, in detail, the factors that influence the performance of this team and we show that the problem that the team members face, when they attempt to recognise one another within the noisy IPD tournament, is exactly analogous to the problem, studied in information theory, of communicating reliably over a noisy channel. Thus we demonstrate that we can use error correcting codes to implement this recognition, and by doing so, further optimise the performance of the team.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In this paper, we present our investigation into the use of a team of players within a noisy Iterated Prisoner?s Dilemma (IPD) tournament. We show that the members of such a team are able to use a pre-arranged sequence of moves that they make at the start of each interaction in order to recognise one another, and that by coordinating their actions they can increase the chances that one of the team members wins the round-robin style tournament. We consider, in detail, the factors that influence the performance of this team and we show that the problem that the team members face, when they attempt to recognise one another within the noisy IPD tournament, is exactly analogous to the problem, studied in information theory, of communicating reliably over a noisy channel. Thus we demonstrate that we can use error correcting codes to implement this recognition, and by doing so, further optimise the performance of the team.
Rogers, Alex; Dash, Rajdeep K.; Ramchurn, Sarvapali D.; Vytelingum, Perukrishnen; Jennings, N. R.
Error-Correcting Codes for Team Coordination within a Noisy Iterated Prisoner?s Dilemma Tournament Book Section
In: Kendel, Graham; Yao, Xin; Chong, Siang Yew (Ed.): The Iterated Prisoners Dilemma Competition: Celebrating the 20th Anniversary, pp. 205–229, World Scientific, 2007.
@incollection{eps263264,
title = {Error-Correcting Codes for Team Coordination within a Noisy Iterated Prisoner?s Dilemma Tournament},
author = {Alex Rogers and Rajdeep K. Dash and Sarvapali D. Ramchurn and Perukrishnen Vytelingum and N. R. Jennings},
editor = {Graham Kendel and Xin Yao and Siang Yew Chong},
url = {http://eprints.soton.ac.uk/263264/},
year = {2007},
date = {2007-01-01},
booktitle = {The Iterated Prisoners Dilemma Competition: Celebrating the 20th Anniversary},
pages = {205–229},
publisher = {World Scientific},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
2006
Karunatillake, N. C.; Jennings, N. R.; Rahwan, I.; Ramchurn, S. D.
Managing Social Influences through Argumentation-Based Negotiation Proceedings Article
In: Third International Workshop on Argumentation in Multi-Agent Systems (ArgMAS 2006), pp. 35–52, 2006, (Event Dates: 8th May 2006).
Abstract | Links | BibTeX | Tags:
@inproceedings{eps262022,
title = {Managing Social Influences through Argumentation-Based Negotiation},
author = {N. C. Karunatillake and N. R. Jennings and I. Rahwan and S. D. Ramchurn},
url = {http://eprints.soton.ac.uk/262022/},
year = {2006},
date = {2006-01-01},
booktitle = {Third International Workshop on Argumentation in Multi-Agent Systems (ArgMAS 2006)},
pages = {35–52},
abstract = {Social influences play an important part in the actions that an individual agent may perform within a multi-agent society. However, the incomplete knowledge and the diverse and conflicting influences present within such societies, may stop an agent from abiding by all its social influences. This may, in turn, lead to conflicts that the agents need to identify, manage, and resolve in order for the society to behave in a coherent manner. To this end, we present an empirical study of an argumentation-based negotiation (ABN) approach that allows the agents to detect such conflicts, and then manage and resolve them through the use of argumentative dialogues. To test our theory, we map our ABN model to a multi-agent task allocation scenario. Our results show that using an argumentation approach allows agents to both efficiently and effectively manage their social influences even under high degrees of incompleteness. Finally, we show that allowing agents to argue and resolve such conflicts early in the negotiation encounter increases their efficiency in managing social influences.},
note = {Event Dates: 8th May 2006},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Social influences play an important part in the actions that an individual agent may perform within a multi-agent society. However, the incomplete knowledge and the diverse and conflicting influences present within such societies, may stop an agent from abiding by all its social influences. This may, in turn, lead to conflicts that the agents need to identify, manage, and resolve in order for the society to behave in a coherent manner. To this end, we present an empirical study of an argumentation-based negotiation (ABN) approach that allows the agents to detect such conflicts, and then manage and resolve them through the use of argumentative dialogues. To test our theory, we map our ABN model to a multi-agent task allocation scenario. Our results show that using an argumentation approach allows agents to both efficiently and effectively manage their social influences even under high degrees of incompleteness. Finally, we show that allowing agents to argue and resolve such conflicts early in the negotiation encounter increases their efficiency in managing social influences.
Ramchurn, S. D.; Sierra, C.; Godo, L.; Jennings, N. R.
Negotiating using rewards Proceedings Article
In: 5th Int. Conf. on Autonomous Agents and Multi-Agent Systems, pp. 400–407, 2006.
Abstract | Links | BibTeX | Tags: Argumentation, Bargaining, Persuasive Negotiation
@inproceedings{eps262591,
title = {Negotiating using rewards},
author = {S. D. Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/262591/},
year = {2006},
date = {2006-01-01},
booktitle = {5th Int. Conf. on Autonomous Agents and Multi-Agent Systems},
journal = {Proc. 5th Int. Conf. on Autonomous Agents and Multi-Agent Systems, Hakodate, Japan},
pages = {400–407},
abstract = {In situations where self-interested agents interact repeatedly, it is important that they are endowed with negotiation techniques that enable them to reach agreements that are profitable in the long run. To this end, we devise a novel negotiation algorithm that generates promises of rewards in future interactions, as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. Moreover, we thus develop a specific negotiation tactic based on this reward generation algorithm and show that it can achieve significantly bettter outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this under concrete settings.},
keywords = {Argumentation, Bargaining, Persuasive Negotiation},
pubstate = {published},
tppubtype = {inproceedings}
}
In situations where self-interested agents interact repeatedly, it is important that they are endowed with negotiation techniques that enable them to reach agreements that are profitable in the long run. To this end, we devise a novel negotiation algorithm that generates promises of rewards in future interactions, as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. Moreover, we thus develop a specific negotiation tactic based on this reward generation algorithm and show that it can achieve significantly bettter outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this under concrete settings.
2005
Ashri, R.; Ramchurn, S. D.; Sabater, J.; Luck, M.; Jennings, N. R.
Trust evaluation through relationship analysis Proceedings Article
In: 4th Int Joint Conf. on Autonomous Agents and Multi-Agent Systems, pp. 1005–1011, 2005.
Abstract | Links | BibTeX | Tags: Multi-Agent Systems., Relationships, Reputation, Trust
@inproceedings{eps260806,
title = {Trust evaluation through relationship analysis},
author = {R. Ashri and S. D. Ramchurn and J. Sabater and M. Luck and N. R. Jennings},
url = {http://eprints.soton.ac.uk/260806/},
year = {2005},
date = {2005-01-01},
booktitle = {4th Int Joint Conf. on Autonomous Agents and Multi-Agent Systems},
journal = {Proceedings: 4th International Joint Conference on Autonomous Agents and Multi-Agent Systems},
pages = {1005–1011},
abstract = {Current mechanisms for evaluating the trustworthiness of an agent within an electronic marketplace depend either on using a history of interactions or on recommendations from other agents. In the first case, these requirements limit what an agent with no prior interaction history can do. In the second case, they transform the problem into one of trusting the recommending agent. However, these mechanisms do not consider the relationships between agents that arise through interactions (such as buying or selling) or through overarching organisational structures (such as hierarchical or flat), which can also aid in evaluating trustworthiness. In response, this paper outlines a method that enables agents to evaluate the trustworthiness of their counterparts, based solely on an analysis of such relationships. Specifically, relationships are identified using a generic technique in conjunction with a basic model for agentbased marketplaces. They are then interpreted through a trust model that enables the inference of trust valuations based on the different types of relationships. In this way, we provide a further component for a trust evaluation model that addresses some of the limitations of existing work.},
keywords = {Multi-Agent Systems., Relationships, Reputation, Trust},
pubstate = {published},
tppubtype = {inproceedings}
}
Current mechanisms for evaluating the trustworthiness of an agent within an electronic marketplace depend either on using a history of interactions or on recommendations from other agents. In the first case, these requirements limit what an agent with no prior interaction history can do. In the second case, they transform the problem into one of trusting the recommending agent. However, these mechanisms do not consider the relationships between agents that arise through interactions (such as buying or selling) or through overarching organisational structures (such as hierarchical or flat), which can also aid in evaluating trustworthiness. In response, this paper outlines a method that enables agents to evaluate the trustworthiness of their counterparts, based solely on an analysis of such relationships. Specifically, relationships are identified using a generic technique in conjunction with a basic model for agentbased marketplaces. They are then interpreted through a trust model that enables the inference of trust valuations based on the different types of relationships. In this way, we provide a further component for a trust evaluation model that addresses some of the limitations of existing work.
Blankenburg, B.; Dash, R. K.; Ramchurn, S. D.; Klusch, M.; Jennings, N. R.
Trusted kernel-based coalition formation Proceedings Article
In: Proc. 4th Int Joint Conf on Autonomous Agents and Multi-Agent Systems, pp. 989–996, 2005.
Abstract | Links | BibTeX | Tags:
@inproceedings{eps260808,
title = {Trusted kernel-based coalition formation},
author = {B. Blankenburg and R. K. Dash and S. D. Ramchurn and M. Klusch and N. R. Jennings},
url = {http://eprints.soton.ac.uk/260808/},
year = {2005},
date = {2005-01-01},
booktitle = {Proc. 4th Int Joint Conf on Autonomous Agents and Multi-Agent Systems},
journal = {Proceedings: 4th International Joint Conference on Autonomous Agents and Multi-agent Systems},
pages = {989–996},
abstract = {We define Trusted Kernel-based Coalition Formation as a novel extension to the traditional kernel-based coalition formation process which ensures agents choose the most reliable coalition partners and are guaranteed to obtain the payment they deserve. To this end, we develop an encryption-based communication protocol and a payment scheme which ensure that agents cannot manipulate the mechanism to their own benefit. Moreover, we integrate a generic trust model in the coalition formation process that permits the selection of the most reliable agents over repeated coalition games. We empirically evaluate our mechanism when iterated and show that, in the long run, it always chooses the coalition structure that has the maximum expected value and determines the payoffs that match their level of reliability.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We define Trusted Kernel-based Coalition Formation as a novel extension to the traditional kernel-based coalition formation process which ensures agents choose the most reliable coalition partners and are guaranteed to obtain the payment they deserve. To this end, we develop an encryption-based communication protocol and a payment scheme which ensure that agents cannot manipulate the mechanism to their own benefit. Moreover, we integrate a generic trust model in the coalition formation process that permits the selection of the most reliable agents over repeated coalition games. We empirically evaluate our mechanism when iterated and show that, in the long run, it always chooses the coalition structure that has the maximum expected value and determines the payoffs that match their level of reliability.
Ramchurn, S. D.; Jennings, N. R.
Trust in agent-based software Book Section
In: Mansell, R.; Collins, B. S. (Ed.): Trust and Crime in Information Societies, pp. 165–204, Elgar Publishing, 2005.
@incollection{eps260823,
title = {Trust in agent-based software},
author = {S. D. Ramchurn and N. R. Jennings},
editor = {R. Mansell and B. S. Collins},
url = {http://eprints.soton.ac.uk/260823/},
year = {2005},
date = {2005-01-01},
booktitle = {Trust and Crime in Information Societies},
pages = {165–204},
publisher = {Elgar Publishing},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
2004
Dash, R. K.; Ramchurn, S. D.; Jennings, N. R.
Trust-Based Mechanism Design Proceedings Article
In: 3rd Int. Conf. on Autonomous Agents and Multi-Agent Systems, pp. 748–755, 2004, (Event Dates: 19-23 July 2004).
Abstract | Links | BibTeX | Tags:
@inproceedings{eps259352,
title = {Trust-Based Mechanism Design},
author = {R. K. Dash and S. D. Ramchurn and N. R. Jennings},
url = {http://eprints.soton.ac.uk/259352/},
year = {2004},
date = {2004-01-01},
booktitle = {3rd Int. Conf. on Autonomous Agents and Multi-Agent Systems},
pages = {748–755},
abstract = {We define trust-based mechanism design as an augmentation of traditional mechanism design in which agents take into account the degree of trust that they have in their counterparts when determining their allocations. To this end, we develop an efficient, individually rational, and incentive compatible mechanism based on trust. This mechanism is embedded in a task allocation scenario in which the trust in an agent is derived from the reported performance success of that agent by all the other agents in the system. We also empirically study the evolution of our mechanism when iterated and show that, in the long run, it always chooses the most successful and cheapest agents to fulfill an allocation and chooses better allocations than other comparable models when faced with biased reporting.},
note = {Event Dates: 19-23 July 2004},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We define trust-based mechanism design as an augmentation of traditional mechanism design in which agents take into account the degree of trust that they have in their counterparts when determining their allocations. To this end, we develop an efficient, individually rational, and incentive compatible mechanism based on trust. This mechanism is embedded in a task allocation scenario in which the trust in an agent is derived from the reported performance success of that agent by all the other agents in the system. We also empirically study the evolution of our mechanism when iterated and show that, in the long run, it always chooses the most successful and cheapest agents to fulfill an allocation and chooses better allocations than other comparable models when faced with biased reporting.
Ramchurn, S. D.; Deitch, B.; Thompson, M. K.; Roure, D. C.; Jennings, N. R.; Luck, M.
Minimising intrusiveness in pervasive computing environments using multi-agent negotiation Proceedings Article
In: First Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous'04), pp. 364–372, IEEE, 2004, (Event Dates: August 22 - 26, 2004).
Abstract | Links | BibTeX | Tags:
@inproceedings{eps259566,
title = {Minimising intrusiveness in pervasive computing environments using multi-agent negotiation},
author = {S. D. Ramchurn and B. Deitch and M. K. Thompson and D. C. Roure and N. R. Jennings and M. Luck},
url = {http://eprints.soton.ac.uk/259566/},
year = {2004},
date = {2004-01-01},
booktitle = {First Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous'04)},
pages = {364–372},
publisher = {IEEE},
abstract = {This paper highlights intrusiveness as a key issue in the field of pervasive computing environments and presents a multi-agent approach to tackling it. Specifically, we discuss how interruptions can impact on individual and group tasks and how they can be managed by taking into account user and group preferences through negotiation between software agents. The system we develop is implemented on the Jabber platform and is deployed in the context of a meeting room scenario.},
note = {Event Dates: August 22 - 26, 2004},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper highlights intrusiveness as a key issue in the field of pervasive computing environments and presents a multi-agent approach to tackling it. Specifically, we discuss how interruptions can impact on individual and group tasks and how they can be managed by taking into account user and group preferences through negotiation between software agents. The system we develop is implemented on the Jabber platform and is deployed in the context of a meeting room scenario.
Ramchurn, S. D.; Huynh, T. D.; Jennings, N. R.
Trust in Multiagent Systems Journal Article
In: The Knowledge Engineering Review, vol. 19, no. 1, pp. 1–25, 2004.
Abstract | Links | BibTeX | Tags:
@article{eps259564,
title = {Trust in Multiagent Systems},
author = {S. D. Ramchurn and T. D. Huynh and N. R. Jennings},
url = {http://eprints.soton.ac.uk/259564/},
year = {2004},
date = {2004-01-01},
journal = {The Knowledge Engineering Review},
volume = {19},
number = {1},
pages = {1–25},
abstract = {Trust is a fundamental concern in large-scale open distributed systems. It lies at the core of all interactions between the entities that have to operate in such uncertain and constantly changing environments. Given this complexity, these components, and the ensuing system, are increasingly being conceptualised, designed, and built using agent-based techniques and, to this end, this paper examines the specific role of trust in multi-agent systems. In particular, we survey the state of the art and provide an account of the main directions along which research efforts are being focused. In so doing, we critically evaluate the relative strengths and weaknesses of the main models that have been proposed and show how, fundamentally, they all seek to minimise the uncertainty in interactions. Finally, we outline the areas that require further research in order to develop a comprehensive treatment of trust in complex computational settings.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Trust is a fundamental concern in large-scale open distributed systems. It lies at the core of all interactions between the entities that have to operate in such uncertain and constantly changing environments. Given this complexity, these components, and the ensuing system, are increasingly being conceptualised, designed, and built using agent-based techniques and, to this end, this paper examines the specific role of trust in multi-agent systems. In particular, we survey the state of the art and provide an account of the main directions along which research efforts are being focused. In so doing, we critically evaluate the relative strengths and weaknesses of the main models that have been proposed and show how, fundamentally, they all seek to minimise the uncertainty in interactions. Finally, we outline the areas that require further research in order to develop a comprehensive treatment of trust in complex computational settings.
Ramchurn, Sarvapali
Multi-Agent Negotiation using Trust and Persuasion PhD Thesis
University of Southampton, 2004.
Abstract | Links | BibTeX | Tags: Argumentation-based Negotiation, multi-agent systems, Negotiation, Persuasion, Trust
@phdthesis{eps260200,
title = {Multi-Agent Negotiation using Trust and Persuasion},
author = {Sarvapali Ramchurn},
url = {http://eprints.soton.ac.uk/260200/},
year = {2004},
date = {2004-01-01},
school = {University of Southampton},
abstract = {In this thesis, we propose a panoply of tools and techniques to manage inter-agent dependencies in open, distributed multi-agent systems that have significant degrees of uncertainty. In particular, we focus on situations in which agents are involved in repeated interactions where they need to negotiate to resolve conflicts that may arise between them. To this end, we endow agents with decision making models that exploit the notion of trust and use persuasive techniques during the negotiation process to reduce the level of uncertainty and achieve better deals in the long run. Firstly, we develop and evaluate a new trust model (called CREDIT) that allows agents to measure the degree of trust they should place in their opponents. This model reduces the uncertainty that agents have about their opponents' reliability. Thus, over repeated interactions, CREDIT enables agents to model their opponents' reliability using probabilistic techniques and a fuzzy reasoning mechanism that allows the combination of measures based on reputation (indirect interactions) and confidence (direct interactions). In so doing, CREDIT takes a wider range of behaviour-influencing factors into account than existing models, including the norms of the agents and the institution within which transactions occur. We then explore a novel application of trust models by showing how the measures developed in CREDIT ca be applied negotiations in multiple encounters. Specifically we show that agents that use CREDIT are able to avoid unreliable agents, both during the selection of interaction partners and during the negotiation process itself by using trust to adjust their negotiation stance. Also, we empirically show that agents are able to reach good deals with agents that are unreliable to some degree (rather than completely unreliable) and with those that try to strategically exploit their opponent. Secondly, having applied CREDIT to negotiations, we further extend the application of trust to reduce uncertainty about the reliability of agents in mechanism design (where the honesty of agents is elicited by the protocol). Thus, we develop $backslash$acftbmd that allows agents using a trust model (such as CREDIT) to reach efficient agreements that choose the most reliable agents in the long run. In particular, we show that our mechanism enforces truth-telling from the agents (i.e. it is incentive compatible), both about their perceived reliability of their opponent and their valuations for the goods to be traded. In proving the latter properties, our trust-based mechanism is shown to be the first reputation mechanism that implements individual rationality, incentive compatibility, and efficiency. Our trust-based mechanism is also empirically evaluated and shown to be better than other comparable models in reaching the outcome that maximises all the negotiating agents' utilities and in choosing the most reliable agents in the long run. Thirdly, having explored ways to reduce uncertainties about reliability and honesty, we use persuasive negotiation techniques to tackle issues associated with uncertainties that agents have about the preferences and the space of possible agreements. To this end, we propose a novel protocol and reasoning mechanism that agents can use to generate and evaluate persuasive elements, such as promises of future rewards, to support the offers they make during negotiation. These persuasive elements aim to make offers more attractive over multiple encounters given the absence of information about an opponent's discount factors or exact payoffs. Specifically, we empirically demonstrate that agents are able to achieve a larger number of agreements and a higher expected utility over repeated encounters when they are given the capability to give or ask for rewards. Moreover, we develop a novel strategy using this protocol and show that it outperforms existing state of the art heuristic negotiation models. Finally, the applicability of persuasive negotiation and CREDIT is exemplified through a practical implementation in a pervasive computing environment. In this context, the negotiation mechanism is implemented in an instant messaging platform (JABBER) and used to resolve conflicts between group and individual preferences that arise in a meeting room scenario. In particular, we show how persuasive negotiation and trust permit a flexible management of interruptions by allowing intrusions to happen at appropriate times during the meeting while still managing to satisfy the preferences of all parties present.},
keywords = {Argumentation-based Negotiation, multi-agent systems, Negotiation, Persuasion, Trust},
pubstate = {published},
tppubtype = {phdthesis}
}
In this thesis, we propose a panoply of tools and techniques to manage inter-agent dependencies in open, distributed multi-agent systems that have significant degrees of uncertainty. In particular, we focus on situations in which agents are involved in repeated interactions where they need to negotiate to resolve conflicts that may arise between them. To this end, we endow agents with decision making models that exploit the notion of trust and use persuasive techniques during the negotiation process to reduce the level of uncertainty and achieve better deals in the long run. Firstly, we develop and evaluate a new trust model (called CREDIT) that allows agents to measure the degree of trust they should place in their opponents. This model reduces the uncertainty that agents have about their opponents' reliability. Thus, over repeated interactions, CREDIT enables agents to model their opponents' reliability using probabilistic techniques and a fuzzy reasoning mechanism that allows the combination of measures based on reputation (indirect interactions) and confidence (direct interactions). In so doing, CREDIT takes a wider range of behaviour-influencing factors into account than existing models, including the norms of the agents and the institution within which transactions occur. We then explore a novel application of trust models by showing how the measures developed in CREDIT ca be applied negotiations in multiple encounters. Specifically we show that agents that use CREDIT are able to avoid unreliable agents, both during the selection of interaction partners and during the negotiation process itself by using trust to adjust their negotiation stance. Also, we empirically show that agents are able to reach good deals with agents that are unreliable to some degree (rather than completely unreliable) and with those that try to strategically exploit their opponent. Secondly, having applied CREDIT to negotiations, we further extend the application of trust to reduce uncertainty about the reliability of agents in mechanism design (where the honesty of agents is elicited by the protocol). Thus, we develop $backslash$acftbmd that allows agents using a trust model (such as CREDIT) to reach efficient agreements that choose the most reliable agents in the long run. In particular, we show that our mechanism enforces truth-telling from the agents (i.e. it is incentive compatible), both about their perceived reliability of their opponent and their valuations for the goods to be traded. In proving the latter properties, our trust-based mechanism is shown to be the first reputation mechanism that implements individual rationality, incentive compatibility, and efficiency. Our trust-based mechanism is also empirically evaluated and shown to be better than other comparable models in reaching the outcome that maximises all the negotiating agents' utilities and in choosing the most reliable agents in the long run. Thirdly, having explored ways to reduce uncertainties about reliability and honesty, we use persuasive negotiation techniques to tackle issues associated with uncertainties that agents have about the preferences and the space of possible agreements. To this end, we propose a novel protocol and reasoning mechanism that agents can use to generate and evaluate persuasive elements, such as promises of future rewards, to support the offers they make during negotiation. These persuasive elements aim to make offers more attractive over multiple encounters given the absence of information about an opponent's discount factors or exact payoffs. Specifically, we empirically demonstrate that agents are able to achieve a larger number of agreements and a higher expected utility over repeated encounters when they are given the capability to give or ask for rewards. Moreover, we develop a novel strategy using this protocol and show that it outperforms existing state of the art heuristic negotiation models. Finally, the applicability of persuasive negotiation and CREDIT is exemplified through a practical implementation in a pervasive computing environment. In this context, the negotiation mechanism is implemented in an instant messaging platform (JABBER) and used to resolve conflicts between group and individual preferences that arise in a meeting room scenario. In particular, we show how persuasive negotiation and trust permit a flexible management of interruptions by allowing intrusions to happen at appropriate times during the meeting while still managing to satisfy the preferences of all parties present.
Ramchurn, Sarvapali; Sierra, C.; Godo, L.; Jennings, N. R.
Devising a trust model for multi-agent interactions using confidence and reputation Journal Article
In: International Journal of Applied Artificial Intelligence, vol. 18, no. 9-10, pp. 833–852, 2004.
@article{eps260155,
title = {Devising a trust model for multi-agent interactions using confidence and reputation},
author = {Sarvapali Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/260155/},
year = {2004},
date = {2004-01-01},
journal = {International Journal of Applied Artificial Intelligence},
volume = {18},
number = {9-10},
pages = {833–852},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2003
Rahwan, I.; Ramchurn, Sarvapali; Jennings, N. R.; McBurney, P.; Parsons, S.; Sonenberg, L.
Argumentation-based negotiation Journal Article
In: The Knowledge Engineering Review, vol. 18, no. 4, pp. 343–375, 2003.
Abstract | Links | BibTeX | Tags:
@article{eps258850,
title = {Argumentation-based negotiation},
author = {I. Rahwan and Sarvapali Ramchurn and N. R. Jennings and P. McBurney and S. Parsons and L. Sonenberg},
url = {http://eprints.soton.ac.uk/258850/},
year = {2003},
date = {2003-01-01},
journal = {The Knowledge Engineering Review},
volume = {18},
number = {4},
pages = {343–375},
abstract = {Negotiation is essential in settings where autonomous agents have con- flicting interests and a desire to cooperate. For this reason, mechanisms in which agents exchange potential agreements according to various rules of interaction have become very popular in recent years as evident, for example, in the auction and mechanism design community. However, a growing body of research is now emerging which points out limitations in such mechanisms and advocates the idea that agents can increase the likelihood and quality of an agreement by exchanging arguments which in- fluence each others? states. This community further argues that argument exchange is sometimes essential when various assumptions about agent rationality cannot be satisfied. To this end, in this article, we identify the main research motivations and ambitions behind work in the field. We then provide a conceptual framework through which we outline the core elements and features required by agents engaged in argumentation-based negotiation, as well as the environment that hosts these agents. For each of these elements, we survey and evaluate existing proposed techniques in the literature and highlight the major challenges that need to be addressed if argument-based negotiation research is to reach its full potential.},
keywords = {},
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Negotiation is essential in settings where autonomous agents have con- flicting interests and a desire to cooperate. For this reason, mechanisms in which agents exchange potential agreements according to various rules of interaction have become very popular in recent years as evident, for example, in the auction and mechanism design community. However, a growing body of research is now emerging which points out limitations in such mechanisms and advocates the idea that agents can increase the likelihood and quality of an agreement by exchanging arguments which in- fluence each others? states. This community further argues that argument exchange is sometimes essential when various assumptions about agent rationality cannot be satisfied. To this end, in this article, we identify the main research motivations and ambitions behind work in the field. We then provide a conceptual framework through which we outline the core elements and features required by agents engaged in argumentation-based negotiation, as well as the environment that hosts these agents. For each of these elements, we survey and evaluate existing proposed techniques in the literature and highlight the major challenges that need to be addressed if argument-based negotiation research is to reach its full potential.
Ramchurn, S. D.; Jennings, N. R.; Sierra, C.
Persuasive negotiation for autonomous agents: A rhetorical approach Proceedings Article
In: IJCAI Workshop on Computational Models of Natural Argument, pp. 9–17, 2003.
Abstract | Links | BibTeX | Tags:
@inproceedings{eps258541,
title = {Persuasive negotiation for autonomous agents: A rhetorical approach},
author = {S. D. Ramchurn and N. R. Jennings and C. Sierra},
url = {http://eprints.soton.ac.uk/258541/},
year = {2003},
date = {2003-01-01},
booktitle = {IJCAI Workshop on Computational Models of Natural Argument},
pages = {9–17},
abstract = {Persuasive negotiation occurs when autonomous agents exchange proposals that are backed up by rhetorical arguments (such as threats, rewards, or appeals). The role of such rhetorical arguments is to persuade the negotiation opponent to accept proposals more readily. To this end, this paper presents a rhetorical model of persuasion that defines the main types of rhetorical particles that are used and that provides a decision making model to enable an agent to determine what type of rhetorical argument to send in a given context and how to evaluate rhetorical arguments that are received. The model is empirically evaluated and we show that it is effective and efficient in reaching agreements.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
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Persuasive negotiation occurs when autonomous agents exchange proposals that are backed up by rhetorical arguments (such as threats, rewards, or appeals). The role of such rhetorical arguments is to persuade the negotiation opponent to accept proposals more readily. To this end, this paper presents a rhetorical model of persuasion that defines the main types of rhetorical particles that are used and that provides a decision making model to enable an agent to determine what type of rhetorical argument to send in a given context and how to evaluate rhetorical arguments that are received. The model is empirically evaluated and we show that it is effective and efficient in reaching agreements.
Ramchurn, Sarvapali; Sierra, C.; Godo, L.; Jennings, N. R.
A computational trust model for multi-agent interactions based on confidence and reputation Proceedings Article
In: 6th International Workshop of Deception, Fraud and Trust in Agent Societies, pp. 69–75, 2003, (Event Dates: 2003).
Abstract | Links | BibTeX | Tags:
@inproceedings{eps258542,
title = {A computational trust model for multi-agent interactions based on confidence and reputation},
author = {Sarvapali Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/258542/},
year = {2003},
date = {2003-01-01},
booktitle = {6th International Workshop of Deception, Fraud and Trust in Agent Societies},
pages = {69–75},
abstract = {In open environments in which autonomous agents can break contracts, computational models of trust have an important role to play in determining who to interact with and how interactions unfold. To this end, we develop such a trust model, based on confi- dence and reputation, and show how it can be concretely applied, using fuzzy sets, to guide agents in evaluating past interactions and in establishing new contracts with one another.},
note = {Event Dates: 2003},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In open environments in which autonomous agents can break contracts, computational models of trust have an important role to play in determining who to interact with and how interactions unfold. To this end, we develop such a trust model, based on confi- dence and reputation, and show how it can be concretely applied, using fuzzy sets, to guide agents in evaluating past interactions and in establishing new contracts with one another.
2002
Panzarasa, P.; Ramchurn, S. D.; Jennings, Nick
Intrusiveness, Trust and Argumentation: Using Automated Negotiation to Inhibit the Transmission of Disruptive Information Proceedings Article
In: Proceedings of the International Conference on Computational Social and Organizational Systems, 2002.
Abstract | Links | BibTeX | Tags:
@inproceedings{eps272014,
title = {Intrusiveness, Trust and Argumentation: Using Automated Negotiation to Inhibit the Transmission of Disruptive Information},
author = {P. Panzarasa and S. D. Ramchurn and Nick Jennings},
url = {http://eprints.soton.ac.uk/272014/},
year = {2002},
date = {2002-01-01},
booktitle = {Proceedings of the International Conference on Computational Social and Organizational Systems},
abstract = {The question of how to promote the growth and diffusion of information has been extensively addressed by a wide research community. A common assumption underpinning most studies is that the information to be transmitted is useful and of high quality. In this paper, we endorse a complementary perspective. We investigate how the growth and diffusion of high quality information can be managed and maximized by preventing, dampening and minimizing the diffusion of low quality, unwanted information. To this end, we focus on the conflict between pervasive computing environments and the joint activities undertaken in parallel local social contexts. When technologies for distributed activities (e.g. mobile technology) develop, both artifacts and services that enable people to participate in non-local contexts are likely to intrude on local situations. As a mechanism for minimizing the intrusion of the technology, we develop a computational model of argumentation-based negotiation among autonomous agents. A key component in the model is played by trust: what arguments are used and how they are evaluated depend on how trustworthy the agents judge one another. To gain an insight into the implications of the model, we conduct a number of virtual experiments. Results enable us to explore how intrusiveness is affected by trust, the negotiation network and the agents' abilities of conducting argumentation.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The question of how to promote the growth and diffusion of information has been extensively addressed by a wide research community. A common assumption underpinning most studies is that the information to be transmitted is useful and of high quality. In this paper, we endorse a complementary perspective. We investigate how the growth and diffusion of high quality information can be managed and maximized by preventing, dampening and minimizing the diffusion of low quality, unwanted information. To this end, we focus on the conflict between pervasive computing environments and the joint activities undertaken in parallel local social contexts. When technologies for distributed activities (e.g. mobile technology) develop, both artifacts and services that enable people to participate in non-local contexts are likely to intrude on local situations. As a mechanism for minimizing the intrusion of the technology, we develop a computational model of argumentation-based negotiation among autonomous agents. A key component in the model is played by trust: what arguments are used and how they are evaluated depend on how trustworthy the agents judge one another. To gain an insight into the implications of the model, we conduct a number of virtual experiments. Results enable us to explore how intrusiveness is affected by trust, the negotiation network and the agents' abilities of conducting argumentation.
61.
Rigas, Emmanouil; Gerding, Enrico; Stein, Sebastian; Ramchurn, Sarvapali D; Bassiliades, Nick
Mechanism Design for Efficient Online and Offline Allocation of Electric Vehicles to Charging Stations Journal Article
In: CoRR, vol. abs/2007.09715, 2020.
@article{DBLP:journals/corr/abs-2007-09715,
title = {Mechanism Design for Efficient Online and Offline Allocation of Electric
Vehicles to Charging Stations},
author = {Emmanouil Rigas and Enrico Gerding and Sebastian Stein and Sarvapali D Ramchurn and Nick Bassiliades},
url = {https://arxiv.org/abs/2007.09715},
year = {2020},
date = {2020-01-01},
journal = {CoRR},
volume = {abs/2007.09715},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
62.
Abeywickrama, Dhaminda B; Cirstea, Corina; Ramchurn, Sarvapali D
Model Checking Human-Agent Collectives for Responsible AI Proceedings Article
In: 2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), pp. 1–8, IEEE 2019.
@inproceedings{abeywickrama2019model,
title = {Model Checking Human-Agent Collectives for Responsible AI},
author = {Dhaminda B Abeywickrama and Corina Cirstea and Sarvapali D Ramchurn},
year = {2019},
date = {2019-01-01},
booktitle = {2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)},
pages = {1–8},
organization = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
63.
Beal, Ryan; Norman, Timothy J; Ramchurn, Sarvapali D
Artificial intelligence for team sports: a survey Journal Article
In: The Knowledge Engineering Review, vol. 34, 2019.
@article{beal2019artificial,
title = {Artificial intelligence for team sports: a survey},
author = {Ryan Beal and Timothy J Norman and Sarvapali D Ramchurn},
year = {2019},
date = {2019-01-01},
journal = {The Knowledge Engineering Review},
volume = {34},
publisher = {Cambridge University Press},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
64.
Abioye, Ayodeji Opeyemi; Prior, Stephen D; Thomas, Glyn T; Saddington, Peter; Ramchurn, Sarvapali D
Multimodal human aerobotic interaction Book Section
In: Unmanned Aerial Vehicles: Breakthroughs in Research and Practice, pp. 142–165, IGI Global, 2019.
@incollection{abioye2019multimodal,
title = {Multimodal human aerobotic interaction},
author = {Ayodeji Opeyemi Abioye and Stephen D Prior and Glyn T Thomas and Peter Saddington and Sarvapali D Ramchurn},
year = {2019},
date = {2019-01-01},
booktitle = {Unmanned Aerial Vehicles: Breakthroughs in Research and Practice},
pages = {142–165},
publisher = {IGI Global},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
65.
Fuentes, Carolina; Porcheron, Martin; Fischer, Joel E; Costanza, Enrico; Malilk, Obaid; Ramchurn, Sarvapali D
Tracking the Consumption of Home Essentials Proceedings Article
In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 639, ACM 2019.
@inproceedings{fuentes2019tracking,
title = {Tracking the Consumption of Home Essentials},
author = {Carolina Fuentes and Martin Porcheron and Joel E Fischer and Enrico Costanza and Obaid Malilk and Sarvapali D Ramchurn},
year = {2019},
date = {2019-01-01},
booktitle = {Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems},
pages = {639},
organization = {ACM},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
66.
Koufakis, Alexandros-Michail; Rigas, Emmanouil S; Bassiliades, Nick; Ramchurn, Sarvapali D
Offline and Online Electric Vehicle Charging Scheduling With V2V Energy Transfer Journal Article
In: IEEE Transactions on Intelligent Transportation Systems, 2019.
@article{koufakis2019offline,
title = {Offline and Online Electric Vehicle Charging Scheduling With V2V Energy Transfer},
author = {Alexandros-Michail Koufakis and Emmanouil S Rigas and Nick Bassiliades and Sarvapali D Ramchurn},
year = {2019},
date = {2019-01-01},
journal = {IEEE Transactions on Intelligent Transportation Systems},
publisher = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
67.
Seitaridis, Andreas; Rigas, Emmanouil S; Bassiliades, Nick; Ramchurn, Sarvapali D
An Agent-based Negotiation Scheme for the Distribution of Electric Vehicles Across a Set of Charging Stations Journal Article
In: Simulation Modelling Practice and Theory, pp. 102040, 2019.
@article{seitaridis2019agent,
title = {An Agent-based Negotiation Scheme for the Distribution of Electric Vehicles Across a Set of Charging Stations},
author = {Andreas Seitaridis and Emmanouil S Rigas and Nick Bassiliades and Sarvapali D Ramchurn},
year = {2019},
date = {2019-01-01},
journal = {Simulation Modelling Practice and Theory},
pages = {102040},
publisher = {Elsevier},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
68.
Abioye, Ayodeji Opeyemi; Prior, Stephen D; Saddington, Peter; Ramchurn, Sarvapali D
Effects of Varying Noise Levels and Lighting Levels on Multimodal Speech and Visual Gesture Interaction with Aerobots Journal Article
In: Applied Sciences, vol. 9, no. 10, pp. 2066, 2019.
@article{abioye2019effects,
title = {Effects of Varying Noise Levels and Lighting Levels on Multimodal Speech and Visual Gesture Interaction with Aerobots},
author = {Ayodeji Opeyemi Abioye and Stephen D Prior and Peter Saddington and Sarvapali D Ramchurn},
year = {2019},
date = {2019-01-01},
journal = {Applied Sciences},
volume = {9},
number = {10},
pages = {2066},
publisher = {Multidisciplinary Digital Publishing Institute},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
69.
Rigas, Emmanouil; Ramchurn, Sarvapali; Bassiliades, Nick
Algorithms for electric vehicle scheduling in large-scale mobility-on-demand schemes Journal Article
In: Artificial Intelligence, vol. 262, pp. 248–278, 2018.
@article{soton422097,
title = {Algorithms for electric vehicle scheduling in large-scale mobility-on-demand schemes},
author = {Emmanouil Rigas and Sarvapali Ramchurn and Nick Bassiliades},
url = {https://eprints.soton.ac.uk/422097/},
year = {2018},
date = {2018-09-01},
journal = {Artificial Intelligence},
volume = {262},
pages = {248–278},
abstract = {We study a setting where Electric Vehicles (EVs) can be hired to drive from pick-up to drop-off points in a Mobility-on-Demand (MoD) scheme. The goal of the system is, either to maximize the number of customers that are serviced, or the total EV utilization. To do so, we characterise the optimisation problem as a max-flow problem in order to determine the set of feasible trips given the available EVs at each location. We then model and solve the EV-to-trip scheduling problem offline and optimally using Mixed Integer Programming (MIP) techniques and show that the solution scales up to medium sized problems. Given this, we develop two non-optimal algorithms, namely an incremental-MIP algorithm for medium to large problems and a greedy heuristic algorithm for very large problems. Moreover, we develop a tabu search-based local search technique to further improve upon and compare against the solution of the non-optimal algorithms. We study the performance of these algorithms in settings where either battery swap or battery charge at each station is used to cope with the EVs' limited driving range. Moreover, in settings where EVs need to be scheduled online, we propose a novel algorithm that accounts for the uncertainty in future trip requests. All algorithms are empirically evaluated using real-world data of locations of shared vehicle pick-up and drop-off stations. In our experiments, we observe that when all EVs carry the same battery which is large enough for the longest trips, the greedy algorithm with battery swap with the max-flow solution as a pre-processing step, provides the optimal solution. At the same time, the greedy algorithm with battery charge is close to the optimal (97% on average) and is further improved when local search is used. When some EVs do not have a large enough battery to execute some of the longest trips, the incremental-MIP generates solutions slightly better than the greedy, while the optimal algorithm is the best but scales up to medium sized problems only. Moreover, the online algorithm is shown to be on average at least 90% of the optimal. Finally, the greedy algorithm scales to 10-times more tasks than the incremental-MIP and 1000-times more than the static MIP in reasonable time.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We study a setting where Electric Vehicles (EVs) can be hired to drive from pick-up to drop-off points in a Mobility-on-Demand (MoD) scheme. The goal of the system is, either to maximize the number of customers that are serviced, or the total EV utilization. To do so, we characterise the optimisation problem as a max-flow problem in order to determine the set of feasible trips given the available EVs at each location. We then model and solve the EV-to-trip scheduling problem offline and optimally using Mixed Integer Programming (MIP) techniques and show that the solution scales up to medium sized problems. Given this, we develop two non-optimal algorithms, namely an incremental-MIP algorithm for medium to large problems and a greedy heuristic algorithm for very large problems. Moreover, we develop a tabu search-based local search technique to further improve upon and compare against the solution of the non-optimal algorithms. We study the performance of these algorithms in settings where either battery swap or battery charge at each station is used to cope with the EVs' limited driving range. Moreover, in settings where EVs need to be scheduled online, we propose a novel algorithm that accounts for the uncertainty in future trip requests. All algorithms are empirically evaluated using real-world data of locations of shared vehicle pick-up and drop-off stations. In our experiments, we observe that when all EVs carry the same battery which is large enough for the longest trips, the greedy algorithm with battery swap with the max-flow solution as a pre-processing step, provides the optimal solution. At the same time, the greedy algorithm with battery charge is close to the optimal (97% on average) and is further improved when local search is used. When some EVs do not have a large enough battery to execute some of the longest trips, the incremental-MIP generates solutions slightly better than the greedy, while the optimal algorithm is the best but scales up to medium sized problems only. Moreover, the online algorithm is shown to be on average at least 90% of the optimal. Finally, the greedy algorithm scales to 10-times more tasks than the incremental-MIP and 1000-times more than the static MIP in reasonable time.
70.
Ayodeji, Opeyemi Abioye; Prior, Stephen; Thomas, Trevor; Saddington, Peter; Ramchurn, Sarvapali D.
The multimodal speech and visual gesture (mSVG) control model for a practical patrol, search, and rescue aerobot Proceedings Article
In: 19th Towards Autonomous Robotic Systems (TAROS) Conference 2018, pp. 423–437, Springer, 2018.
@inproceedings{soton418869,
title = {The multimodal speech and visual gesture (mSVG) control model for a practical patrol, search, and rescue aerobot},
author = {Opeyemi Abioye Ayodeji and Stephen Prior and Trevor Thomas and Peter Saddington and Sarvapali D. Ramchurn},
url = {https://eprints.soton.ac.uk/418869/},
year = {2018},
date = {2018-07-01},
booktitle = {19th Towards Autonomous Robotic Systems (TAROS) Conference 2018},
volume = {10965},
pages = {423–437},
publisher = {Springer},
abstract = {This paper describes a model of the multimodal speech and visual gesture (mSVG) control for aerobots operating at higher nCA autonomy levels, within the context of a patrol, search, and rescue application. The developed mSVG control architecture, its mathematical navigation model, and some high level command operation models were discussed. This was successfully tested using both MATLAB simulation and python based ROS Gazebo UAV simulations. Some limitations were identified, which formed the basis for the further works presented.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
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This paper describes a model of the multimodal speech and visual gesture (mSVG) control for aerobots operating at higher nCA autonomy levels, within the context of a patrol, search, and rescue application. The developed mSVG control architecture, its mathematical navigation model, and some high level command operation models were discussed. This was successfully tested using both MATLAB simulation and python based ROS Gazebo UAV simulations. Some limitations were identified, which formed the basis for the further works presented.
71.
Ortega, Andre P; Merrett, Geoff; Ramchurn, Sarvapali
Automated negotiation for opportunistic energy trading between neighbouring wireless sensor networks Proceedings Article
In: 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (31/10/18), 2018.
@inproceedings{soton423060,
title = {Automated negotiation for opportunistic energy trading between neighbouring wireless sensor networks},
author = {Andre P Ortega and Geoff Merrett and Sarvapali Ramchurn},
url = {https://eprints.soton.ac.uk/423060/},
year = {2018},
date = {2018-07-01},
booktitle = {2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (31/10/18)},
abstract = {As the Internet of Things grows, the number of wireless sensor networks deployed in close proximity will continue to increase. By nature, these networks are limited by the battery supply that determines their lifetime and system utility. To counter such a shortcoming, energy harvesting technologies have become increasingly investigated to provide a perpetual energy source; however, new problems arise as a result of their wide spatio-temporal variation. In this paper, we propose opportunistic energy trading, which enables otherwise independent networks to be sustained by sharing resources. Our goal is to provide a novel cooperation model based on negotiation to solve coordination conflicts between energy harvesting wireless sensor networks. Results show that networks are able to satisfy their loads when they agree to cooperate.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
As the Internet of Things grows, the number of wireless sensor networks deployed in close proximity will continue to increase. By nature, these networks are limited by the battery supply that determines their lifetime and system utility. To counter such a shortcoming, energy harvesting technologies have become increasingly investigated to provide a perpetual energy source; however, new problems arise as a result of their wide spatio-temporal variation. In this paper, we propose opportunistic energy trading, which enables otherwise independent networks to be sustained by sharing resources. Our goal is to provide a novel cooperation model based on negotiation to solve coordination conflicts between energy harvesting wireless sensor networks. Results show that networks are able to satisfy their loads when they agree to cooperate.
72.
Ayodeji, Opeyemi Abioye; Prior, Stephen; Thomas, Trevor; Saddington, Peter; Ramchurn, Sarvapali
Quantifying the effects of varying light-visibility and noise-sound levels in practical multimodal speech and visual gesture (mSVG) interaction with aerobots Proceedings Article
In: IEEE International Conference on Applied System Innovation (IEEE ICASI) 2018, pp. 842–845, IEEE, 2018.
@inproceedings{soton418871,
title = {Quantifying the effects of varying light-visibility and noise-sound levels in practical multimodal speech and visual gesture (mSVG) interaction with aerobots},
author = {Opeyemi Abioye Ayodeji and Stephen Prior and Trevor Thomas and Peter Saddington and Sarvapali Ramchurn},
url = {https://eprints.soton.ac.uk/418871/},
year = {2018},
date = {2018-06-01},
booktitle = {IEEE International Conference on Applied System Innovation (IEEE ICASI) 2018},
pages = {842–845},
publisher = {IEEE},
abstract = {This paper discusses the research work conducted to quantify the effective range of lighting levels and ambient noise levels in order to inform the design and development of a multimodal speech and visual gesture (mSVG) control interface for the control of a UAV. Noise level variation from 55 dB to 85 dB is observed under control lab conditions to determine where speech commands for a UAV fails, and to consider why, and possibly suggest a solution around this. Similarly, lighting levels are varied within the control lab condition to determine a range of effective visibility levels. The limitation of this work and some further work from this were also presented.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper discusses the research work conducted to quantify the effective range of lighting levels and ambient noise levels in order to inform the design and development of a multimodal speech and visual gesture (mSVG) control interface for the control of a UAV. Noise level variation from 55 dB to 85 dB is observed under control lab conditions to determine where speech commands for a UAV fails, and to consider why, and possibly suggest a solution around this. Similarly, lighting levels are varied within the control lab condition to determine a range of effective visibility levels. The limitation of this work and some further work from this were also presented.
73.
Garcia, Pedro Garcia; Costanza, Enrico; Verame, Jhim; Nowacka, Diana; Ramchurn, Sarvapali D
Seeing (movement) is believing: the effect of motion on perception of automatic systems performance Journal Article
In: Human-Computer Interaction, pp. 1-51, 2018.
@article{soton422967,
title = {Seeing (movement) is believing: the effect of motion on perception of automatic systems performance},
author = {Pedro Garcia Garcia and Enrico Costanza and Jhim Verame and Diana Nowacka and Sarvapali D Ramchurn},
url = {https://eprints.soton.ac.uk/422967/},
year = {2018},
date = {2018-04-01},
journal = {Human-Computer Interaction},
pages = {1-51},
abstract = {ensuremath<pensuremath>In this article, we report on one lab study and seven follow-up studies on a crowdsourcing platform designed to investigate the potential of animation cues to influence users? perception of two smart systems: a handwriting recognition and a part-of-speech tagging system. Results from the first three studies indicate that animation cues can influence a participant?s perception of both systems? performance. The subsequent three studies, designed to try and identify an explanation for this effect, suggest that this effect is related to the participants? mental model of the smart system. The last two studies were designed to characterize the effect more in detail, and they revealed that different amounts of animation do not seem to create substantial differences and that the effect persists even when the system?s performance decreases, but only when the difference in performance level between the systems being compared is small.ensuremath</pensuremath>},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
ensuremath<pensuremath>In this article, we report on one lab study and seven follow-up studies on a crowdsourcing platform designed to investigate the potential of animation cues to influence users? perception of two smart systems: a handwriting recognition and a part-of-speech tagging system. Results from the first three studies indicate that animation cues can influence a participant?s perception of both systems? performance. The subsequent three studies, designed to try and identify an explanation for this effect, suggest that this effect is related to the participants? mental model of the smart system. The last two studies were designed to characterize the effect more in detail, and they revealed that different amounts of animation do not seem to create substantial differences and that the effect persists even when the system?s performance decreases, but only when the difference in performance level between the systems being compared is small.ensuremath</pensuremath>
74.
Bicego, M.; Farinelli, A.; Grosso, E.; Paolini, D.; Ramchurn, S. D.
On the distinctiveness of the electricity load profile Journal Article
In: Pattern Recognition, vol. 74, no. Supplement C, pp. 317–325, 2018, ISSN: 0031-3203.
@article{BICEGO2018317b,
title = {On the distinctiveness of the electricity load profile},
author = {M. Bicego and A. Farinelli and E. Grosso and D. Paolini and S. D. Ramchurn},
url = {http://www.sciencedirect.com/science/article/pii/S0031320317303904},
doi = {https://doi.org/10.1016/j.patcog.2017.09.039},
issn = {0031-3203},
year = {2018},
date = {2018-01-01},
journal = {Pattern Recognition},
volume = {74},
number = {Supplement C},
pages = {317–325},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
75.
Olabambo, Ifeoluwa Oluwasuji; Malik, Obaid; Zhang, Jie; Ramchurn, Sarvapali
Algorithms for fair load shedding in developing countries Proceedings Article
In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), pp. 1590-1596, 2018.
@inproceedings{soton420541,
title = {Algorithms for fair load shedding in developing countries},
author = {Ifeoluwa Oluwasuji Olabambo and Obaid Malik and Jie Zhang and Sarvapali Ramchurn},
url = {https://eprints.soton.ac.uk/420541/},
year = {2018},
date = {2018-01-01},
booktitle = {Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI)},
pages = {1590-1596},
abstract = {Due to the limited generation capacity of power stations, many developing countries frequently resort to disconnecting large parts of the power grid from supply, a process termed load shedding. During load shedding, many homes are left without electricity, causing them inconvenience and discomfort. In this paper, we present a number of optimization heuristics that focus on pairwise and groupwise fairness, such that households (i.e. agents) are fairly allocated electricity. We evaluate the heuristics against standard fairness metrics in terms of comfort delivered to homes, as well as the number of times they are disconnected from electricity supply. Thus, we establish new benchmarks for fair load shedding schemes.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Due to the limited generation capacity of power stations, many developing countries frequently resort to disconnecting large parts of the power grid from supply, a process termed load shedding. During load shedding, many homes are left without electricity, causing them inconvenience and discomfort. In this paper, we present a number of optimization heuristics that focus on pairwise and groupwise fairness, such that households (i.e. agents) are fairly allocated electricity. We evaluate the heuristics against standard fairness metrics in terms of comfort delivered to homes, as well as the number of times they are disconnected from electricity supply. Thus, we establish new benchmarks for fair load shedding schemes.
76.
Olabambo, Ifeoluwa Oluwasuji; Malik, Obaid; Zhang, Jie; Ramchurn, Sarvapali
Algorithms to manage load shedding events in developing countries Proceedings Article
In: Proceedings of the International Conference on Autonomous and Multi-Agent Systems (AAMAS), pp. 2034-2036, 2018.
@inproceedings{soton420127,
title = {Algorithms to manage load shedding events in developing countries},
author = {Ifeoluwa Oluwasuji Olabambo and Obaid Malik and Jie Zhang and Sarvapali Ramchurn},
url = {https://eprints.soton.ac.uk/420127/},
year = {2018},
date = {2018-01-01},
booktitle = {Proceedings of the International Conference on Autonomous and Multi-Agent Systems (AAMAS)},
pages = {2034-2036},
abstract = {Due to the limited generation capacity of power stations, many developing countries frequently resort to disconnecting large parts of the power grid from supply, a process termed load shedding. This leaves homes without electricity, causing them discomfort and inconvenience. Because fairness is not a priority when shedding load, some homes bear the brunt of these effects. In this paper, we present our ongoing research into considering fairness when shedding load at the household level.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Due to the limited generation capacity of power stations, many developing countries frequently resort to disconnecting large parts of the power grid from supply, a process termed load shedding. This leaves homes without electricity, causing them discomfort and inconvenience. Because fairness is not a priority when shedding load, some homes bear the brunt of these effects. In this paper, we present our ongoing research into considering fairness when shedding load at the household level.
77.
Kiel, Manzano Verame Jhim; Costanza, Enrico; Ramchurn, Sarvapali; Fischer, Joel; Crabtree, Andy; Rodden, Tom; Jennings, Nick
Learning from the veg box: Designing unpredictability in agency delegation Proceedings Article
In: CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, ACM, 2018.
@inproceedings{soton417370,
title = {Learning from the veg box: Designing unpredictability in agency delegation},
author = {Manzano Verame Jhim Kiel and Enrico Costanza and Sarvapali Ramchurn and Joel Fischer and Andy Crabtree and Tom Rodden and Nick Jennings},
url = {https://eprints.soton.ac.uk/417370/},
year = {2018},
date = {2018-01-01},
booktitle = {CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems},
publisher = {ACM},
abstract = {The Internet of Things (IoT) promises to enable applications that foster a more efficient, sustainable, and healthy way of life. If end-users are to take full advantage of these developments we foresee the need for future IoT systems and services to include an element of autonomy and support the delegation of agency to software processes and connected devices. To inform the design of such future technology, we report on a breaching experiment designed to investigate how people integrate an unpredictable service, through the veg box scheme, in everyday life. Findings from our semistructured interviews and a two-week diary study with 11 households reveal that agency delegation must be warranted, that it must be possible to incorporate delegated decisions into everyday activities, and that delegation is subject to constraint. We further discuss design implications on the need to support people?s diverse values, and their coordinative and creative practices.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The Internet of Things (IoT) promises to enable applications that foster a more efficient, sustainable, and healthy way of life. If end-users are to take full advantage of these developments we foresee the need for future IoT systems and services to include an element of autonomy and support the delegation of agency to software processes and connected devices. To inform the design of such future technology, we report on a breaching experiment designed to investigate how people integrate an unpredictable service, through the veg box scheme, in everyday life. Findings from our semistructured interviews and a two-week diary study with 11 households reveal that agency delegation must be warranted, that it must be possible to incorporate delegated decisions into everyday activities, and that delegation is subject to constraint. We further discuss design implications on the need to support people?s diverse values, and their coordinative and creative practices.
78.
Vu, Huan; Aknine, Samir; Ramchurn, Sarvapali D
A Decentralised Approach to Intersection Traffic Management Proceedings Article
In: Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI 2018, July 13-19, 2018, Stockholm, Sweden., pp. 527–533, 2018.
@inproceedings{DBLP:conf/ijcai/VuAR18,
title = {A Decentralised Approach to Intersection Traffic Management},
author = {Huan Vu and Samir Aknine and Sarvapali D Ramchurn},
url = {https://doi.org/10.24963/ijcai.2018/73},
doi = {10.24963/ijcai.2018/73},
year = {2018},
date = {2018-01-01},
booktitle = {Proceedings of the Twenty-Seventh International Joint Conference on
Artificial Intelligence, IJCAI 2018, July 13-19, 2018, Stockholm,
Sweden.},
pages = {527–533},
crossref = {DBLP:conf/ijcai/2018},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
79.
Khan, Md. Mosaddek; -, Long Tran; Ramchurn, Sarvapali D; Jennings, Nicholas R
Speeding Up GDL-Based Message Passing Algorithms for Large-Scale DCOPs Journal Article
In: Comput. J., vol. 61, no. 11, pp. 1639–1666, 2018.
@article{DBLP:journals/cj/KhanTRJ18,
title = {Speeding Up GDL-Based Message Passing Algorithms for Large-Scale DCOPs},
author = {Md. Mosaddek Khan and Long Tran - and Sarvapali D Ramchurn and Nicholas R Jennings},
url = {https://doi.org/10.1093/comjnl/bxy021},
doi = {10.1093/comjnl/bxy021},
year = {2018},
date = {2018-01-01},
journal = {Comput. J.},
volume = {61},
number = {11},
pages = {1639–1666},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
80.
Rigas, Emmanouil S; Karapostolakis, Sotiris; Bassiliades, Nick; Ramchurn, Sarvapali D
EVLibSim: A tool for the simulation of electric vehicles' charging stations using the EVLib library Journal Article
In: Simulation Modelling Practice and Theory, vol. 87, pp. 99–119, 2018.
@article{DBLP:journals/simpra/RigasKBR18,
title = {EVLibSim: A tool for the simulation of electric vehicles' charging
stations using the EVLib library},
author = {Emmanouil S Rigas and Sotiris Karapostolakis and Nick Bassiliades and Sarvapali D Ramchurn},
url = {https://doi.org/10.1016/j.simpat.2018.06.007},
doi = {10.1016/j.simpat.2018.06.007},
year = {2018},
date = {2018-01-01},
journal = {Simulation Modelling Practice and Theory},
volume = {87},
pages = {99–119},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Selected Publications
Multi-agent signal-less intersection management with dynamic platoon formation
No data available.
https://eprints.soton.ac.uk/478647/
@inproceedings{soton478647,
title = {Multi-agent signal-less intersection management with dynamic platoon formation},
author = {Phuriwat Worrawichaipat and Enrico Gerding and Ioannis Kaparias and Sarvapali Ramchurn},
url = {https://eprints.soton.ac.uk/478647/},
year = {2023},
date = {2023-05-01},
booktitle = {22nd International Conference on Autonomous Agents and Multiagent Systems (29/05/23 - 02/06/23)},
pages = {1542--1550},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Multi-agent signal-less intersection management with dynamic platoon formation},
author = {Phuriwat Worrawichaipat and Enrico Gerding and Ioannis Kaparias and Sarvapali Ramchurn},
url = {https://eprints.soton.ac.uk/478647/},
year = {2023},
date = {2023-05-01},
booktitle = {22nd International Conference on Autonomous Agents and Multiagent Systems (29/05/23 - 02/06/23)},
pages = {1542--1550},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
AI Foundation Models: initial review, CMA Consultation, TAS Hub Response
No data available.
https://eprints.soton.ac.uk/477553/
@misc{soton477553,
title = {AI Foundation Models: initial review, CMA Consultation, TAS Hub Response},
author = {Joshua Krook and Derek McAuley and Stuart Anderson and John Downer and Peter Winter and Sarvapali D Ramchurn},
url = {https://eprints.soton.ac.uk/477553/},
year = {2023},
date = {2023-06-01},
publisher = {University of Southampton},
keywords = {},
pubstate = {published},
tppubtype = {misc}
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title = {AI Foundation Models: initial review, CMA Consultation, TAS Hub Response},
author = {Joshua Krook and Derek McAuley and Stuart Anderson and John Downer and Peter Winter and Sarvapali D Ramchurn},
url = {https://eprints.soton.ac.uk/477553/},
year = {2023},
date = {2023-06-01},
publisher = {University of Southampton},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
The effect of data visualisation quality and task density on human-swarm interaction
No data available.
https://eprints.soton.ac.uk/479970/
@inproceedings{soton479970,
title = {The effect of data visualisation quality and task density on human-swarm interaction},
author = {Ayodeji Abioye and Mohammad Naiseh and William Hunt and Jediah R Clark and Sarvapali D Ramchurn and Mohammad Soorati},
url = {https://eprints.soton.ac.uk/479970/},
year = {2023},
date = {2023-06-01},
booktitle = {Proceedings of the 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)},
publisher = {IEEE},
abstract = {Despite the advantages of having robot swarms, human supervision is required for real-world applications. The performance of the human-swarm system depends on several factors including the data availability for the human operators. In this paper, we study the human factors aspect of the human-swarm interaction and investigate how having access to high-quality data can affect the performance of the human-swarm system - the number of tasks completed and the human trust level in operation. We designed an experiment where a human operator is tasked to operate a swarm to identify casualties in an area within a given time period. One group of operators had the option to request high-quality pictures while the other group had to base their decision on the available low-quality images. We performed a user study with 120 participants and recorded their success rate (directly logged via the simulation platform) as well as their workload and trust level (measured through a questionnaire after completing a human-swarm scenario). The findings from our study indicated that the group granted access to high-quality data exhibited an increased workload and placed greater trust in the swarm, thus confirming our initial hypothesis. However, we also found that the number of accurately identified casualties did not significantly vary between the two groups, suggesting that data quality had no impact on the successful completion of tasks.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {The effect of data visualisation quality and task density on human-swarm interaction},
author = {Ayodeji Abioye and Mohammad Naiseh and William Hunt and Jediah R Clark and Sarvapali D Ramchurn and Mohammad Soorati},
url = {https://eprints.soton.ac.uk/479970/},
year = {2023},
date = {2023-06-01},
booktitle = {Proceedings of the 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)},
publisher = {IEEE},
abstract = {Despite the advantages of having robot swarms, human supervision is required for real-world applications. The performance of the human-swarm system depends on several factors including the data availability for the human operators. In this paper, we study the human factors aspect of the human-swarm interaction and investigate how having access to high-quality data can affect the performance of the human-swarm system - the number of tasks completed and the human trust level in operation. We designed an experiment where a human operator is tasked to operate a swarm to identify casualties in an area within a given time period. One group of operators had the option to request high-quality pictures while the other group had to base their decision on the available low-quality images. We performed a user study with 120 participants and recorded their success rate (directly logged via the simulation platform) as well as their workload and trust level (measured through a questionnaire after completing a human-swarm scenario). The findings from our study indicated that the group granted access to high-quality data exhibited an increased workload and placed greater trust in the swarm, thus confirming our initial hypothesis. However, we also found that the number of accurately identified casualties did not significantly vary between the two groups, suggesting that data quality had no impact on the successful completion of tasks.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Demonstrating performance benefits of human-swarm teaming
Autonomous swarms of robots can bring robustness, scalability and adaptability to safety-critical tasks such as search and rescue but their application is still very limited. Using semi-autonomous swarms with human control can bring robot swarms to real-world applications. Human operators can define goals for the swarm, monitor their performance and interfere with, or overrule, the decisions and behaviour. We present the "Human And Robot Interactive Swarm'' simulator (HARIS) that allows multi-user interaction with a robot swarm and facilitates qualitative and quantitative user studies through simulation of robot swarms completing tasks, from package delivery to search and rescue, with varying levels of human control. In this demonstration, we showcase the simulator by using it to study the performance gain offered by maintaining a "human-in-the-loop'' over a fully autonomous system as an example. This is illustrated in the context of search and rescue, with an autonomous allocation of resources to those in need.
https://eprints.soton.ac.uk/479903/
@inproceedings{soton479903,
title = {Demonstrating performance benefits of human-swarm teaming},
author = {William Hunt and Jack Ryan and Ayodeji O Abioye and Sarvapali D Ramchurn and Mohammad D Soorati},
url = {https://eprints.soton.ac.uk/479903/},
year = {2023},
date = {2023-05-01},
booktitle = {Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems},
pages = {3062--3064},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)},
abstract = {Autonomous swarms of robots can bring robustness, scalability and adaptability to safety-critical tasks such as search and rescue but their application is still very limited. Using semi-autonomous swarms with human control can bring robot swarms to real-world applications. Human operators can define goals for the swarm, monitor their performance and interfere with, or overrule, the decisions and behaviour. We present the "Human And Robot Interactive Swarm'' simulator (HARIS) that allows multi-user interaction with a robot swarm and facilitates qualitative and quantitative user studies through simulation of robot swarms completing tasks, from package delivery to search and rescue, with varying levels of human control. In this demonstration, we showcase the simulator by using it to study the performance gain offered by maintaining a "human-in-the-loop'' over a fully autonomous system as an example. This is illustrated in the context of search and rescue, with an autonomous allocation of resources to those in need.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Demonstrating performance benefits of human-swarm teaming},
author = {William Hunt and Jack Ryan and Ayodeji O Abioye and Sarvapali D Ramchurn and Mohammad D Soorati},
url = {https://eprints.soton.ac.uk/479903/},
year = {2023},
date = {2023-05-01},
booktitle = {Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems},
pages = {3062--3064},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)},
abstract = {Autonomous swarms of robots can bring robustness, scalability and adaptability to safety-critical tasks such as search and rescue but their application is still very limited. Using semi-autonomous swarms with human control can bring robot swarms to real-world applications. Human operators can define goals for the swarm, monitor their performance and interfere with, or overrule, the decisions and behaviour. We present the "Human And Robot Interactive Swarm'' simulator (HARIS) that allows multi-user interaction with a robot swarm and facilitates qualitative and quantitative user studies through simulation of robot swarms completing tasks, from package delivery to search and rescue, with varying levels of human control. In this demonstration, we showcase the simulator by using it to study the performance gain offered by maintaining a "human-in-the-loop'' over a fully autonomous system as an example. This is illustrated in the context of search and rescue, with an autonomous allocation of resources to those in need.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
2012
Ebden, Mark; Huynh, Trung Dong; Moreau, Luc; Ramchurn, Sarvapali; Stephen, Roberts
Network analysis on provenance graphs from a crowdsourcing application Proceedings Article
In: Groth, Paul; Frew, James (Ed.): 4th International Provenance and Annotation Workshop, pp. 168–182, 2012.
@inproceedings{eps340068,
title = {Network analysis on provenance graphs from a crowdsourcing application},
author = {Mark Ebden and Trung Dong Huynh and Luc Moreau and Sarvapali Ramchurn and Roberts Stephen},
editor = {Paul Groth and James Frew},
url = {http://eprints.soton.ac.uk/340068/},
year = {2012},
date = {2012-01-01},
booktitle = {4th International Provenance and Annotation Workshop},
volume = {7525},
pages = {168–182},
series = {0302-9743},
abstract = {Crowdsourcing has become a popular means for quickly achieving various tasks in large quantities. CollabMap is an online mapping application in which we crowdsource the identification of evacuation routes in residential areas to be used for planning large-scale evacuations. So far, approximately 38,000 micro-tasks have been completed by over 100 contributors. In order to assist with data verification, we introduced provenance tracking into the application, and approximately 5,000 provenance graphs have been generated. They have provided us various insights into the typical characteristics of provenance graphs in the crowdsourcing context. In particular, we have estimated probability distribution functions over three selected characteristics of these provenance graphs: the node degree, the graph diameter, and the densification exponent. We describe methods to define these three characteristics across specific combinations of node types and edge types, and present our findings in this paper. Applications of our methods include rapid comparison of one provenance graph versus another, or of one style of provenance database versus another. Our results also indicate that provenance graphs represent a suitable area of exploitation for existing network analysis tools concerned with modelling, prediction, and the inference of missing nodes and edges.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Crowdsourcing has become a popular means for quickly achieving various tasks in large quantities. CollabMap is an online mapping application in which we crowdsource the identification of evacuation routes in residential areas to be used for planning large-scale evacuations. So far, approximately 38,000 micro-tasks have been completed by over 100 contributors. In order to assist with data verification, we introduced provenance tracking into the application, and approximately 5,000 provenance graphs have been generated. They have provided us various insights into the typical characteristics of provenance graphs in the crowdsourcing context. In particular, we have estimated probability distribution functions over three selected characteristics of these provenance graphs: the node degree, the graph diameter, and the densification exponent. We describe methods to define these three characteristics across specific combinations of node types and edge types, and present our findings in this paper. Applications of our methods include rapid comparison of one provenance graph versus another, or of one style of provenance database versus another. Our results also indicate that provenance graphs represent a suitable area of exploitation for existing network analysis tools concerned with modelling, prediction, and the inference of missing nodes and edges.
Matthews, Tim; Ramchurn, Sarvapali; Chalkiadakis, Georgios
Competing with humans at fantasy football: team formation in large partially-observable domains Proceedings Article
In: Proceedings of the Twenty-Sixth Conference on Artificial Intelligence, pp. 1394–1400, Association for the Advancement of Artificial Intelligence, 2012.
@inproceedings{eps340382,
title = {Competing with humans at fantasy football: team formation in large partially-observable domains},
author = {Tim Matthews and Sarvapali Ramchurn and Georgios Chalkiadakis},
url = {http://eprints.soton.ac.uk/340382/},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings of the Twenty-Sixth Conference on Artificial Intelligence},
pages = {1394–1400},
publisher = {Association for the Advancement of Artificial Intelligence},
abstract = {We present the first real-world benchmark for sequentially optimal team formation, working within the framework of a class of online football prediction games known as Fantasy Football. We model the problem as a Bayesian reinforcement learning one, where the action space is exponential in the number of players and where the decision maker?s beliefs are over multiple characteristics of each footballer. We then exploit domain knowledge to construct computationally tractable solution techniques in order to build a competitive automated Fantasy Football manager. Thus, we are able to establish the baseline performance in this domain, even without complete information on footballers? performances (accessible to human managers), showing that our agent is able to rank at around the top percentile when pitched against 2.5M human players},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We present the first real-world benchmark for sequentially optimal team formation, working within the framework of a class of online football prediction games known as Fantasy Football. We model the problem as a Bayesian reinforcement learning one, where the action space is exponential in the number of players and where the decision maker?s beliefs are over multiple characteristics of each footballer. We then exploit domain knowledge to construct computationally tractable solution techniques in order to build a competitive automated Fantasy Football manager. Thus, we are able to establish the baseline performance in this domain, even without complete information on footballers? performances (accessible to human managers), showing that our agent is able to rank at around the top percentile when pitched against 2.5M human players
Miller, Sam; Ramchurn, Sarvapali D; Rogers, Alex
Optimal Decentralised Dispatch of Embedded Generation in the Smart Grid Journal Article
In: In Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2012.
@article{eps273142,
title = {Optimal Decentralised Dispatch of Embedded Generation in the Smart Grid},
author = {Sam Miller and Sarvapali D Ramchurn and Alex Rogers},
url = {http://eprints.soton.ac.uk/273142/},
year = {2012},
date = {2012-01-01},
booktitle = {Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS)},
journal = {In Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS)},
abstract = {Distribution network operators face a number of challenges; capacity constrained networks, and balancing electricity demand with generation from intermittent renewable resources. Thus, there is an increasing need for scalable approaches to facilitate optimal dispatch in the distribution network. To this end, we cast the optimal dispatch problem as a decentralised agent-based coordination problem and formalise it as a DCOP. We show how this can be decomposed as a factor graph and solved in a decentralised manner using algorithms based on the generalised distributive law; in particular, the max-sum algorithm. We go on to show that max-sum applied na?vely in this setting performs a large number of redundant computations. To address this issue, we present a novel decentralised message passing algorithm using dynamic programming that outperforms max-sum by pruning the search space. We empirically evaluate our algorithm using real distribution network data, showing that it outperforms (in terms of computational time and total size of messages sent) both a centralised approach, which uses IBM?s ILOG CPLEX 12.2, and max-sum, for large networks.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Distribution network operators face a number of challenges; capacity constrained networks, and balancing electricity demand with generation from intermittent renewable resources. Thus, there is an increasing need for scalable approaches to facilitate optimal dispatch in the distribution network. To this end, we cast the optimal dispatch problem as a decentralised agent-based coordination problem and formalise it as a DCOP. We show how this can be decomposed as a factor graph and solved in a decentralised manner using algorithms based on the generalised distributive law; in particular, the max-sum algorithm. We go on to show that max-sum applied na?vely in this setting performs a large number of redundant computations. To address this issue, we present a novel decentralised message passing algorithm using dynamic programming that outperforms max-sum by pruning the search space. We empirically evaluate our algorithm using real distribution network data, showing that it outperforms (in terms of computational time and total size of messages sent) both a centralised approach, which uses IBM?s ILOG CPLEX 12.2, and max-sum, for large networks.
Ramchurn, Sarvapali; Vytelingum, Perukrishnen; Rogers, Alex; Jennings, Nicholas R.
Putting the Smarts into the Smart Grid: A Grand Challenge for Artificial Intelligence Journal Article
In: Communications of the ACM, vol. 55, no. 4, pp. 86–97, 2012.
@article{eps272606,
title = {Putting the Smarts into the Smart Grid: A Grand Challenge for Artificial Intelligence},
author = {Sarvapali Ramchurn and Perukrishnen Vytelingum and Alex Rogers and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/272606/},
year = {2012},
date = {2012-01-01},
journal = {Communications of the ACM},
volume = {55},
number = {4},
pages = {86–97},
publisher = {ACM},
abstract = {The phenomenal growth in material wealth experienced in developed countries throughout the twentieth century has largely been driven by the availability of cheap energy derived from fossil fuels (originally coal, then oil, and most recently natural gas). However, the continued availability of this cheap energy cannot be taken for granted given the growing concern that increasing demand for these fuels (and particularly, demand for oil) will outstrip our ability to produce them (so called `peak oil'). Many mature oil and gas fields around the world have already peaked and their annual production is now steadily declining. Predictions of when world oil production will peak vary between 0-20 years into the future, but even the most conservative estimates provide little scope for complacency given the significant price increases that peak oil is likely to precipitate. Furthermore, many of the oil and gas reserves that do remain are in environmentally or politically sensitive regions of the world where threats to supply create increased price volatility (as evidenced by the 2010 Deepwater Horizon disaster and 2011 civil unrest in the Middle East). Finally, the growing consensus on the long term impact of carbon emissions from burning fossil fuels suggests that even if peak oil is avoided, and energy security assured, a future based on fossil fuel use will expose regions of the world to damaging climate change that will make the lives of many of the world's poorest people even harder.},
keywords = {},
pubstate = {published},
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}
The phenomenal growth in material wealth experienced in developed countries throughout the twentieth century has largely been driven by the availability of cheap energy derived from fossil fuels (originally coal, then oil, and most recently natural gas). However, the continued availability of this cheap energy cannot be taken for granted given the growing concern that increasing demand for these fuels (and particularly, demand for oil) will outstrip our ability to produce them (so called `peak oil'). Many mature oil and gas fields around the world have already peaked and their annual production is now steadily declining. Predictions of when world oil production will peak vary between 0-20 years into the future, but even the most conservative estimates provide little scope for complacency given the significant price increases that peak oil is likely to precipitate. Furthermore, many of the oil and gas reserves that do remain are in environmentally or politically sensitive regions of the world where threats to supply create increased price volatility (as evidenced by the 2010 Deepwater Horizon disaster and 2011 civil unrest in the Middle East). Finally, the growing consensus on the long term impact of carbon emissions from burning fossil fuels suggests that even if peak oil is avoided, and energy security assured, a future based on fossil fuel use will expose regions of the world to damaging climate change that will make the lives of many of the world's poorest people even harder.
Ramchurn, Sarvapali D.; Gerding, Enrico; Jennings, N. R.; Hu, Jun
Practical distributed coalition formation via heuristic negotiation in social networks Proceedings Article
In: Fifth International Workshop on Optimisation in Multi-Agent Systems (OPTMAS), 2012.
@inproceedings{eps344492,
title = {Practical distributed coalition formation via heuristic negotiation in social networks},
author = {Sarvapali D. Ramchurn and Enrico Gerding and N. R. Jennings and Jun Hu},
url = {http://eprints.soton.ac.uk/344492/},
year = {2012},
date = {2012-01-01},
booktitle = {Fifth International Workshop on Optimisation in Multi-Agent Systems (OPTMAS)},
abstract = {We present a novel framework for decentralised coalition formation in social networks, where agents can form coalitions through bilateral negotiations with their neighbours. Specifically, we present a practical negotiation protocol and decision functions that enable agents to form coalitions with agents beyond their peers. Building on this, we establish baseline negotiation strategies which we empirically show to be efficient (agreements are reached in few negotiation rounds) and effective (agreements have high utility compared to a centralised approach) on a variety of network topologies. Moreover, we show that the average degree of social networks can significantly affect the performance of these strategies.},
keywords = {},
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We present a novel framework for decentralised coalition formation in social networks, where agents can form coalitions through bilateral negotiations with their neighbours. Specifically, we present a practical negotiation protocol and decision functions that enable agents to form coalitions with agents beyond their peers. Building on this, we establish baseline negotiation strategies which we empirically show to be efficient (agreements are reached in few negotiation rounds) and effective (agreements have high utility compared to a centralised approach) on a variety of network topologies. Moreover, we show that the average degree of social networks can significantly affect the performance of these strategies.
Richardson, Darren P.; Costanza, Enrico; Ramchurn, Sarvapali D.
Evaluating semi-automatic annotation of domestic energy consumption as a memory aid Proceedings Article
In: UbiComp '12 Proceedings of the 2012 ACM Conference on Ubiquitous Computing, pp. 613–614, 2012.
@inproceedings{eps349083,
title = {Evaluating semi-automatic annotation of domestic energy consumption as a memory aid},
author = {Darren P. Richardson and Enrico Costanza and Sarvapali D. Ramchurn},
url = {http://eprints.soton.ac.uk/349083/},
year = {2012},
date = {2012-01-01},
booktitle = {UbiComp '12 Proceedings of the 2012 ACM Conference on Ubiquitous Computing},
pages = {613–614},
abstract = {Frequent feedback about energy consumption can help conservation, one of the current global challenges. Such feedback is most helpful if users can relate it to their own day-to-day activities. In earlier work we showed that manual annotation of domestic energy consumption logs aids users to make such connection and discover patterns they were not aware of. In this poster we report how we augmented manual annotation with machine learning classification techniques. We propose the design of a lab study to evaluate the system, extending methods used to evaluate context aware memory aids, and we present the results of a pilot with 5 participants.},
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Frequent feedback about energy consumption can help conservation, one of the current global challenges. Such feedback is most helpful if users can relate it to their own day-to-day activities. In earlier work we showed that manual annotation of domestic energy consumption logs aids users to make such connection and discover patterns they were not aware of. In this poster we report how we augmented manual annotation with machine learning classification techniques. We propose the design of a lab study to evaluate the system, extending methods used to evaluate context aware memory aids, and we present the results of a pilot with 5 participants.
Rogers, Alex; Ramchurn, Sarvapali; Jennings, Nicholas R.
Delivering the smart grid: Challenges for autonomous agents and multi-agent systems research Proceedings Article
In: Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12), pp. 2166–2172, 2012.
@inproceedings{eps337560,
title = {Delivering the smart grid: Challenges for autonomous agents and multi-agent systems research},
author = {Alex Rogers and Sarvapali Ramchurn and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/337560/},
year = {2012},
date = {2012-01-01},
booktitle = {Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12)},
pages = {2166–2172},
abstract = {Restructuring electricity grids to meet the increased demand caused by the electrification of transport and heating, while making greater use of intermittent renewable energy sources, represents one of the greatest engineering challenges of our day. This modern electric- ity grid, in which both electricity and information flow in two directions between large numbers of widely dis- tributed suppliers and generators – commonly termed the ?smart grid? – represents a radical reengineering of infrastructure which has changed little over the last hundred years. However, the autonomous behaviour expected of the smart grid, its distributed nature, and the existence of multiple stakeholders each with their own incentives and interests, challenges existing engineering approaches. In this challenge paper, we describe why we believe that artificial intelligence, and particularly, the fields of autonomous agents and multi-agent systems are essential for delivering the smart grid as it is envisioned. We present some recent work in this area and describe many of the challenges that still remain.},
keywords = {},
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Restructuring electricity grids to meet the increased demand caused by the electrification of transport and heating, while making greater use of intermittent renewable energy sources, represents one of the greatest engineering challenges of our day. This modern electric- ity grid, in which both electricity and information flow in two directions between large numbers of widely dis- tributed suppliers and generators – commonly termed the ?smart grid? – represents a radical reengineering of infrastructure which has changed little over the last hundred years. However, the autonomous behaviour expected of the smart grid, its distributed nature, and the existence of multiple stakeholders each with their own incentives and interests, challenges existing engineering approaches. In this challenge paper, we describe why we believe that artificial intelligence, and particularly, the fields of autonomous agents and multi-agent systems are essential for delivering the smart grid as it is envisioned. We present some recent work in this area and describe many of the challenges that still remain.
Truong, Ngoc Cuong; Tran-Thanh, Long; Costanza, Enrico; Ramchurn, Sarvapali D.
Predicting energy consumption activities for home energy management Proceedings Article
In: Agent Technologies for Energy Systems (ATES 2012), 2012.
@inproceedings{eps339215,
title = {Predicting energy consumption activities for home energy management},
author = {Ngoc Cuong Truong and Long Tran-Thanh and Enrico Costanza and Sarvapali D. Ramchurn},
url = {http://eprints.soton.ac.uk/339215/},
year = {2012},
date = {2012-01-01},
booktitle = {Agent Technologies for Energy Systems (ATES 2012)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
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Voice, Thomas; Ramchurn, Sarvapali; Jennings, Nick
On coalition formation with sparse synergies Proceedings Article
In: Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), pp. 223–230, 2012.
@inproceedings{eps273083,
title = {On coalition formation with sparse synergies},
author = {Thomas Voice and Sarvapali Ramchurn and Nick Jennings},
url = {http://eprints.soton.ac.uk/273083/},
year = {2012},
date = {2012-01-01},
booktitle = {Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS)},
pages = {223–230},
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Simpson, Edwin; Reece, Steven; Penta, Antonio; Ramchurn, Sarvapali D
Using a Bayesian Model to Combine LDA Features with Crowdsourced Responses Proceedings Article
In: Proceedings of The Twenty-First Text REtrieval Conference, TREC 2012, Gaithersburg, Maryland, USA, November 6-9, 2012, 2012.
@inproceedings{DBLP:conf/trec/SimpsonRPR12,
title = {Using a Bayesian Model to Combine LDA Features with Crowdsourced
Responses},
author = {Edwin Simpson and Steven Reece and Antonio Penta and Sarvapali D Ramchurn},
url = {http://trec.nist.gov/pubs/trec21/papers/HAC.crowd.final.pdf},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings of The Twenty-First Text REtrieval Conference, TREC
2012, Gaithersburg, Maryland, USA, November 6-9, 2012},
crossref = {DBLP:conf/trec/2012},
keywords = {},
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2011
Alam, Muddasser; Rogers, Alex; Ramchurn, Sarvapali
A negotiation protocol for multiple interdependent issues negotiation over energy exchange Proceedings Article
In: IJCAI Workshop on AI for an Intelligent Planet, 2011, (Event Dates: July-16).
@inproceedings{eps272479,
title = {A negotiation protocol for multiple interdependent issues negotiation over energy exchange},
author = {Muddasser Alam and Alex Rogers and Sarvapali Ramchurn},
url = {http://eprints.soton.ac.uk/272479/},
year = {2011},
date = {2011-01-01},
booktitle = {IJCAI Workshop on AI for an Intelligent Planet},
abstract = {We present a novel negotiation protocol to facilitate energy exchange between off-grid homes that are equipped with renewable energy generation and electricity storage. Our solution imposes additional constraints on negotiation such that it reduces a complex interdependent multi-issue problem to one that is tractable. We prove that using our protocol, agents can reach a Pareto-optimal, dominant strategy equilibrium in a decentralized and timely fashion. We empirically evaluate our approach in a realistic setting. In this case, we show that energy exchange can be useful in reducing the capacity of the energy storage devices in homes by close to 40%},
note = {Event Dates: July-16},
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We present a novel negotiation protocol to facilitate energy exchange between off-grid homes that are equipped with renewable energy generation and electricity storage. Our solution imposes additional constraints on negotiation such that it reduces a complex interdependent multi-issue problem to one that is tractable. We prove that using our protocol, agents can reach a Pareto-optimal, dominant strategy equilibrium in a decentralized and timely fashion. We empirically evaluate our approach in a realistic setting. In this case, we show that energy exchange can be useful in reducing the capacity of the energy storage devices in homes by close to 40%
Macarthur, Kathryn; Stranders, Ruben; Ramchurn, Sarvapali; Jennings, Nick
A Distributed Anytime Algorithm for Dynamic Task Allocation in Multi-Agent Systems Proceedings Article
In: Twenty-Fifth Conference on Artificial Intelligence (AAAI), pp. 701–706, AAAI Press, 2011, (Event Dates: August 7-11, 2011).
@inproceedings{eps272233,
title = {A Distributed Anytime Algorithm for Dynamic Task Allocation in Multi-Agent Systems},
author = {Kathryn Macarthur and Ruben Stranders and Sarvapali Ramchurn and Nick Jennings},
url = {http://eprints.soton.ac.uk/272233/},
year = {2011},
date = {2011-01-01},
booktitle = {Twenty-Fifth Conference on Artificial Intelligence (AAAI)},
pages = {701–706},
publisher = {AAAI Press},
abstract = {We introduce a novel distributed algorithm for multi-agent task allocation problems where the sets of tasks and agents constantly change over time. We build on an existing anytime algorithm (fast-max-sum), and give it significant new capa- bilities: namely, an online pruning procedure that simplifies the problem, and a branch-and-bound technique that reduces the search space. This allows us to scale to problems with hundreds of tasks and agents. We empirically evaluate our algorithm against established benchmarks and find that, even in such large environments, a solution is found up to 31% faster, and with up to 23% more utility, than state-of-the-art approximation algorithms. In addition, our algorithm sends up to 30% fewer messages than current approaches when the set of agents or tasks changes.},
note = {Event Dates: August 7-11, 2011},
keywords = {},
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}
We introduce a novel distributed algorithm for multi-agent task allocation problems where the sets of tasks and agents constantly change over time. We build on an existing anytime algorithm (fast-max-sum), and give it significant new capa- bilities: namely, an online pruning procedure that simplifies the problem, and a branch-and-bound technique that reduces the search space. This allows us to scale to problems with hundreds of tasks and agents. We empirically evaluate our algorithm against established benchmarks and find that, even in such large environments, a solution is found up to 31% faster, and with up to 23% more utility, than state-of-the-art approximation algorithms. In addition, our algorithm sends up to 30% fewer messages than current approaches when the set of agents or tasks changes.
Macarthur, Kathryn; Vinyals, Meritxell; Farinelli, Alessandro; Ramchurn, Sarvapali; Jennings, Nick
Decentralised Parallel Machine Scheduling for Multi-Agent Task Allocation Proceedings Article
In: Fourth International Workshop on Optimisation in Multi-Agent Systems, 2011, (Event Dates: May 3, 2011).
@inproceedings{eps272234,
title = {Decentralised Parallel Machine Scheduling for Multi-Agent Task Allocation},
author = {Kathryn Macarthur and Meritxell Vinyals and Alessandro Farinelli and Sarvapali Ramchurn and Nick Jennings},
url = {http://eprints.soton.ac.uk/272234/},
year = {2011},
date = {2011-01-01},
booktitle = {Fourth International Workshop on Optimisation in Multi-Agent Systems},
abstract = {Multi-agent task allocation problems pervade a wide range of real-world applications, such as search and rescue in disaster manage- ment, or grid computing. In these applications, where agents are given tasks to perform in parallel, it is often the case that the performance of all agents is judged based on the time taken by the slowest agent to complete its tasks. Hence, efficient distribution of tasks across het- erogeneous agents is important to ensure a short completion time. An equivalent problem to this can be found in operations research, and is known as scheduling jobs on unrelated parallel machines (also known as Rensuremath|ensuremath|Cmax). In this paper, we draw parallels between unrelated parallel machine scheduling and multi-agent task allocation problems, and, in so doing, we present the decentralised task distribution algorithm (DTDA), the first decentralised solution to Rensuremath|ensuremath|Cmax. Empirical evaluation of the DTDA is shown to generate solutions within 86?97% of the optimal on sparse graphs, in the best case, whilst providing a very good estimate (within 1%) of the global solution at each agent.},
note = {Event Dates: May 3, 2011},
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Multi-agent task allocation problems pervade a wide range of real-world applications, such as search and rescue in disaster manage- ment, or grid computing. In these applications, where agents are given tasks to perform in parallel, it is often the case that the performance of all agents is judged based on the time taken by the slowest agent to complete its tasks. Hence, efficient distribution of tasks across het- erogeneous agents is important to ensure a short completion time. An equivalent problem to this can be found in operations research, and is known as scheduling jobs on unrelated parallel machines (also known as Rensuremath|ensuremath|Cmax). In this paper, we draw parallels between unrelated parallel machine scheduling and multi-agent task allocation problems, and, in so doing, we present the decentralised task distribution algorithm (DTDA), the first decentralised solution to Rensuremath|ensuremath|Cmax. Empirical evaluation of the DTDA is shown to generate solutions within 86?97% of the optimal on sparse graphs, in the best case, whilst providing a very good estimate (within 1%) of the global solution at each agent.
Osborne, Michael A.; Rogers, Alex; Roberts, Stephen J.; Ramchurn, Sarvapali D.; Jennings, Nicholas R.
Gaussian Processes for Time Series Prediction Book Section
In: Bayesian Time Series Models, pp. 341–360, Cambridge University Press, 2011, (Chapter: 16).
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title = {Gaussian Processes for Time Series Prediction},
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year = {2011},
date = {2011-01-01},
booktitle = {Bayesian Time Series Models},
pages = {341–360},
publisher = {Cambridge University Press},
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Ramchurn, Sarvapali; Vytelingum, Perukrishnen; Rogers, Alex; Jennings, Nick
Agent-based homeostatic control for green energy in the smart grid Journal Article
In: ACM Transactions on Intelligent Systems and Technology, vol. 2, no. 4, pp. 35:1–35:28, 2011.
@article{eps272015,
title = {Agent-based homeostatic control for green energy in the smart grid},
author = {Sarvapali Ramchurn and Perukrishnen Vytelingum and Alex Rogers and Nick Jennings},
url = {http://eprints.soton.ac.uk/272015/},
year = {2011},
date = {2011-01-01},
journal = {ACM Transactions on Intelligent Systems and Technology},
volume = {2},
number = {4},
pages = {35:1–35:28},
abstract = {With dwindling non-renewable energy reserves and the adverse effects of climate change, the development of the smart electricity grid is seen as key to solving global energy security issues and to reducing carbon emissions. In this respect, there is a growing need to integrate renewable (or green) energy sources in the grid. However, the intermittency of these energy sources requires that demand must also be made more responsive to changes in supply, and a number of smart grid technologies are being developed, such as high-capacity batteries and smart meters for the home, to enable consumers to be more responsive to conditions on the grid in real-time. Traditional solutions based on these technologies, however, tend to ignore the fact that individual consumers will behave in such a way that best satisfies their own preferences to use or store energy (as opposed to that of the supplier or the grid operator). Hence, in practice, it is unclear how these solutions will cope with large numbers of consumers using their devices in this way. Against this background, in this paper, we develop novel control mechanisms based on the use of autonomous agents to better incorporate consumer preferences in managing demand. These agents, residing on consumers' smart meters, can both communicate with the grid and optimise their owner's energy consumption to satisfy their preferences. More specifically, we provide a novel control mechanism that models and controls a system comprising of a green energy supplier operating within the grid and a number of individual homes (each possibly owning a storage device). This control mechanism is based on the concept of homeostasis whereby control signals are sent to individual components of a system, based on their continuous feedback, in order to change their state so that the system may reach a stable equilibrium. Thus, we define a new carbon-based pricing mechanism for this green energy supplier that takes advantage of carbon-intensity signals available on the internet in order to provide real-time pricing. The pricing scheme is designed in such a way that it can be readily implemented using existing communication technologies and is easily understandable by consumers. Building upon this, we develop new control signals that the supplier can use to incentivise agents to shift demand (using their storage device) to times when green energy is available. Moreover, we show how these signals can be adapted according to changes in supply and to various degrees of penetration of storage in the system. We empirically evaluate our system and show that, when all homes are equipped with storage devices, the supplier can significantly reduce its reliance on other carbon-emitting power sources to cater for its own shortfalls. By so doing, the supplier reduces the carbon emission of the system by up to 25% while the consumer reduces its costs by up to 14.5%. Finally, we demonstrate that our homeostatic control mechanism is not sensitive to small prediction errors and the supplier is incentivised to accurately predict its green production to minimise costs.},
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}
With dwindling non-renewable energy reserves and the adverse effects of climate change, the development of the smart electricity grid is seen as key to solving global energy security issues and to reducing carbon emissions. In this respect, there is a growing need to integrate renewable (or green) energy sources in the grid. However, the intermittency of these energy sources requires that demand must also be made more responsive to changes in supply, and a number of smart grid technologies are being developed, such as high-capacity batteries and smart meters for the home, to enable consumers to be more responsive to conditions on the grid in real-time. Traditional solutions based on these technologies, however, tend to ignore the fact that individual consumers will behave in such a way that best satisfies their own preferences to use or store energy (as opposed to that of the supplier or the grid operator). Hence, in practice, it is unclear how these solutions will cope with large numbers of consumers using their devices in this way. Against this background, in this paper, we develop novel control mechanisms based on the use of autonomous agents to better incorporate consumer preferences in managing demand. These agents, residing on consumers' smart meters, can both communicate with the grid and optimise their owner's energy consumption to satisfy their preferences. More specifically, we provide a novel control mechanism that models and controls a system comprising of a green energy supplier operating within the grid and a number of individual homes (each possibly owning a storage device). This control mechanism is based on the concept of homeostasis whereby control signals are sent to individual components of a system, based on their continuous feedback, in order to change their state so that the system may reach a stable equilibrium. Thus, we define a new carbon-based pricing mechanism for this green energy supplier that takes advantage of carbon-intensity signals available on the internet in order to provide real-time pricing. The pricing scheme is designed in such a way that it can be readily implemented using existing communication technologies and is easily understandable by consumers. Building upon this, we develop new control signals that the supplier can use to incentivise agents to shift demand (using their storage device) to times when green energy is available. Moreover, we show how these signals can be adapted according to changes in supply and to various degrees of penetration of storage in the system. We empirically evaluate our system and show that, when all homes are equipped with storage devices, the supplier can significantly reduce its reliance on other carbon-emitting power sources to cater for its own shortfalls. By so doing, the supplier reduces the carbon emission of the system by up to 25% while the consumer reduces its costs by up to 14.5%. Finally, we demonstrate that our homeostatic control mechanism is not sensitive to small prediction errors and the supplier is incentivised to accurately predict its green production to minimise costs.
Ramchurn, Sarvapali; Vytelingum, Perukrishnen; Rogers, Alex; Jennings, Nick
Agent-based control for decentralised demand side management in the smart grid Proceedings Article
In: The Tenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), pp. 5–12, 2011.
@inproceedings{eps271985,
title = {Agent-based control for decentralised demand side management in the smart grid},
author = {Sarvapali Ramchurn and Perukrishnen Vytelingum and Alex Rogers and Nick Jennings},
url = {http://eprints.soton.ac.uk/271985/},
year = {2011},
date = {2011-01-01},
booktitle = {The Tenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011)},
pages = {5–12},
abstract = {Central to the vision of the smart grid is the deployment of smart meters that will allow autonomous software agents, representing the consumers, to optimise their use of devices and heating in the smart home while interacting with the grid. However, without some form of coordination, the population of agents may end up with overly-homogeneous optimised consumption patterns that may generate significant peaks in demand in the grid. These peaks, in turn, reduce the efficiency of the overall system, increase carbon emissions, and may even, in the worst case, cause blackouts. Hence, in this paper, we introduce a novel model of a Decentralised Demand Side Management (DDSM) mechanism that allows agents, by adapting the deferment of their loads based on grid prices, to coordinate in a decentralised manner. Specifically, using average UK consumption profiles for 26M homes, we demonstrate that, through an emergent coordination of the agents, the peak demand of domestic consumers in the grid can be reduced by up to 17% and carbon emissions by up to 6%. We also show that our DDSM mechanism is robust to the increasing electrification of heating in UK homes (i.e. it exhibits a similar efficiency).},
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Central to the vision of the smart grid is the deployment of smart meters that will allow autonomous software agents, representing the consumers, to optimise their use of devices and heating in the smart home while interacting with the grid. However, without some form of coordination, the population of agents may end up with overly-homogeneous optimised consumption patterns that may generate significant peaks in demand in the grid. These peaks, in turn, reduce the efficiency of the overall system, increase carbon emissions, and may even, in the worst case, cause blackouts. Hence, in this paper, we introduce a novel model of a Decentralised Demand Side Management (DDSM) mechanism that allows agents, by adapting the deferment of their loads based on grid prices, to coordinate in a decentralised manner. Specifically, using average UK consumption profiles for 26M homes, we demonstrate that, through an emergent coordination of the agents, the peak demand of domestic consumers in the grid can be reduced by up to 17% and carbon emissions by up to 6%. We also show that our DDSM mechanism is robust to the increasing electrification of heating in UK homes (i.e. it exhibits a similar efficiency).
Stranders, Ruben; Ramchurn, Sarvapali; Shi, Bing; Jennings, Nick
CollabMap: Augmenting Maps using the Wisdom of Crowds Proceedings Article
In: Third Human Computation Workshop, 2011.
@inproceedings{eps272478,
title = {CollabMap: Augmenting Maps using the Wisdom of Crowds},
author = {Ruben Stranders and Sarvapali Ramchurn and Bing Shi and Nick Jennings},
url = {http://eprints.soton.ac.uk/272478/},
year = {2011},
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Voice, Thomas; Vytelingum, Perukrishnen; Ramchurn, Sarvapali; Rogers, Alex; Jennings, Nick
Decentralised Control of Micro-Storage in the Smart Grid Proceedings Article
In: AAAI-11: Twenty-Fifth Conference on Artificial Intelligence, pp. 1421–1426, 2011, (Event Dates: August 7?11, 2011).
@inproceedings{eps272262,
title = {Decentralised Control of Micro-Storage in the Smart Grid},
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year = {2011},
date = {2011-01-01},
booktitle = {AAAI-11: Twenty-Fifth Conference on Artificial Intelligence},
pages = {1421–1426},
abstract = {In this paper, we propose a novel decentralised control mechanism to manage micro-storage in the smart grid. Our approach uses an adaptive pricing scheme that energy suppliers apply to home smart agents controlling micro-storage devices. In particular, we prove that the interaction between a supplier using our pricing scheme and the actions of selfish micro-storage agents forms a globally stable feedback loop that converges to an efficient equilibrium. We further propose a market strategy that allows the supplier to reduce wholesale purchasing costs without increasing the uncertainty and variance for its aggregate consumer demand. Moreover, we empirically evaluate our mechanism (based on the UK grid data) and show that it yields savings of up to 16% in energy cost for consumers using storage devices with average capacity 10 kWh. Furthermore, we show that it is robust against extreme system changes.},
note = {Event Dates: August 7?11, 2011},
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In this paper, we propose a novel decentralised control mechanism to manage micro-storage in the smart grid. Our approach uses an adaptive pricing scheme that energy suppliers apply to home smart agents controlling micro-storage devices. In particular, we prove that the interaction between a supplier using our pricing scheme and the actions of selfish micro-storage agents forms a globally stable feedback loop that converges to an efficient equilibrium. We further propose a market strategy that allows the supplier to reduce wholesale purchasing costs without increasing the uncertainty and variance for its aggregate consumer demand. Moreover, we empirically evaluate our mechanism (based on the UK grid data) and show that it yields savings of up to 16% in energy cost for consumers using storage devices with average capacity 10 kWh. Furthermore, we show that it is robust against extreme system changes.
Vytelingum, Perukrishnen; Voice, Thomas; Ramchurn, Sarvapali; Rogers, Alex; Jennings, Nick
Theoretical and practical foundations of large-scale agent-based micro-storage in the smart grid Journal Article
In: Journal of Artificial Intelligence Research, vol. 42, pp. 765–813, 2011, (AAMAS 2010 iRobot Best Paper Award).
@article{eps272961,
title = {Theoretical and practical foundations of large-scale agent-based micro-storage in the smart grid},
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url = {http://eprints.soton.ac.uk/272961/},
year = {2011},
date = {2011-01-01},
journal = {Journal of Artificial Intelligence Research},
volume = {42},
pages = {765–813},
abstract = {In this paper, we present a novel decentralised management technique that allows electricity micro-storage devices, deployed within individual homes as part of a smart electricity grid, to converge to profitable and efficient behaviours. Specifically, we propose the use of software agents, residing on the users' smart meters, to automate and optimise the charging cycle of micro-storage devices in the home to minimise its costs, and we present a study of both the theoretical underpinnings and the implications of a practical solution, of using software agents for such micro-storage management. First, by formalising the strategic choice each agent makes in deciding when to charge its battery, we develop a game-theoretic framework within which we can analyse the competitive equilibria of an electricity grid populated by such agents and hence predict the best consumption profile for that population given their battery properties and individual load profiles. Our framework also allows us to compute theoretical bounds on the amount of storage that will be adopted by the population. Second, to analyse the practical implications of micro-storage deployments in the grid, we present a novel algorithm that each agent can use to optimise its battery storage profile in order to minimise its owner's costs. This algorithm uses a learning strategy that allows it to adapt as the price of electricity changes in real-time, and we show that the adoption of these strategies results in the system converging to the theoretical equilibria. Finally, we empirically evaluate the adoption of our micro-storage management technique within a complex setting, based on the UK electricity market, where agents may have widely varying load profiles, battery types, and learning rates. In this case, our approach yields savings of up to 14% in energy cost for an average consumer using a storage device with a capacity of less than 4.5 kWh and up to a 7% reduction in carbon emissions resulting from electricity generation (with only domestic consumers adopting micro-storage and, commercial and industrial consumers not changing their demand). Moreover, corroborating our theoretical bound, an equilibrium is shown to exist where no more than 48% of households would wish to own storage devices and where social welfare would also be improved (yielding overall annual savings of nearly pounds1.5B).},
note = {AAMAS 2010 iRobot Best Paper Award},
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In this paper, we present a novel decentralised management technique that allows electricity micro-storage devices, deployed within individual homes as part of a smart electricity grid, to converge to profitable and efficient behaviours. Specifically, we propose the use of software agents, residing on the users' smart meters, to automate and optimise the charging cycle of micro-storage devices in the home to minimise its costs, and we present a study of both the theoretical underpinnings and the implications of a practical solution, of using software agents for such micro-storage management. First, by formalising the strategic choice each agent makes in deciding when to charge its battery, we develop a game-theoretic framework within which we can analyse the competitive equilibria of an electricity grid populated by such agents and hence predict the best consumption profile for that population given their battery properties and individual load profiles. Our framework also allows us to compute theoretical bounds on the amount of storage that will be adopted by the population. Second, to analyse the practical implications of micro-storage deployments in the grid, we present a novel algorithm that each agent can use to optimise its battery storage profile in order to minimise its owner's costs. This algorithm uses a learning strategy that allows it to adapt as the price of electricity changes in real-time, and we show that the adoption of these strategies results in the system converging to the theoretical equilibria. Finally, we empirically evaluate the adoption of our micro-storage management technique within a complex setting, based on the UK electricity market, where agents may have widely varying load profiles, battery types, and learning rates. In this case, our approach yields savings of up to 14% in energy cost for an average consumer using a storage device with a capacity of less than 4.5 kWh and up to a 7% reduction in carbon emissions resulting from electricity generation (with only domestic consumers adopting micro-storage and, commercial and industrial consumers not changing their demand). Moreover, corroborating our theoretical bound, an equilibrium is shown to exist where no more than 48% of households would wish to own storage devices and where social welfare would also be improved (yielding overall annual savings of nearly pounds1.5B).
2010
Macarthur, Kathryn; Farinelli, Alessandro; Ramchurn, Sarvapali; Jennings, Nick
Efficient, Superstabilizing Decentralised Optimisation for Dynamic Task Allocation Environments Proceedings Article
In: Third International Workshop on: Optimisation in Multi-Agent Systems (OptMas) at the Ninth Joint Conference on Autonomous and Multi-Agent Systems, pp. 25–32, 2010, (Event Dates: 10 May 2010).
@inproceedings{eps268588,
title = {Efficient, Superstabilizing Decentralised Optimisation for Dynamic Task Allocation Environments},
author = {Kathryn Macarthur and Alessandro Farinelli and Sarvapali Ramchurn and Nick Jennings},
url = {http://eprints.soton.ac.uk/268588/},
year = {2010},
date = {2010-01-01},
booktitle = {Third International Workshop on: Optimisation in Multi-Agent Systems (OptMas) at the Ninth Joint Conference on Autonomous and Multi-Agent Systems},
pages = {25–32},
abstract = {Decentralised optimisation is a key issue for multi-agent systems, and while many solution techniques have been developed, few provide support for dynamic environments, which change over time, such as disaster management. Given this, in this paper, we present Bounded Fast Max Sum (BFMS): a novel, dynamic, superstabilizing algorithm which provides a bounded approximate solution to certain classes of distributed constraint optimisation problems. We achieve this by eliminating dependencies in the constraint functions, according to how much impact they have on the overall solution value. In more detail, we propose iGHS, which computes a maximum spanning tree on subsections of the constraint graph, in order to reduce communication and computation overheads. Given this, we empirically evaluate BFMS, which shows that BFMS reduces communication and computation done by Bounded Max Sum by up to 99%, while obtaining 60-88% of the optimal utility.},
note = {Event Dates: 10 May 2010},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Decentralised optimisation is a key issue for multi-agent systems, and while many solution techniques have been developed, few provide support for dynamic environments, which change over time, such as disaster management. Given this, in this paper, we present Bounded Fast Max Sum (BFMS): a novel, dynamic, superstabilizing algorithm which provides a bounded approximate solution to certain classes of distributed constraint optimisation problems. We achieve this by eliminating dependencies in the constraint functions, according to how much impact they have on the overall solution value. In more detail, we propose iGHS, which computes a maximum spanning tree on subsections of the constraint graph, in order to reduce communication and computation overheads. Given this, we empirically evaluate BFMS, which shows that BFMS reduces communication and computation done by Bounded Max Sum by up to 99%, while obtaining 60-88% of the optimal utility.
Ramchurn, S. D.; Polukarov, Mariya; Farinelli, Alessandro; Jennings, Nick; Trong, Cuong
Coalition Formation with Spatial and Temporal Constraints Proceedings Article
In: International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2010), pp. 1181–1188, 2010, (Event Dates: May 2010).
@inproceedings{eps268497,
title = {Coalition Formation with Spatial and Temporal Constraints},
author = {S. D. Ramchurn and Mariya Polukarov and Alessandro Farinelli and Nick Jennings and Cuong Trong},
url = {http://eprints.soton.ac.uk/268497/},
year = {2010},
date = {2010-01-01},
booktitle = {International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2010)},
pages = {1181–1188},
abstract = {The coordination of emergency responders and robots to undertake a number of tasks in disaster scenarios is a grand challenge for multi-agent systems. Central to this endeavour is the problem of forming the best teams (coalitions) of responders to perform the various tasks in the area where the disaster has struck. Moreover, these teams may have to form, disband, and reform in different areas of the disaster region. This is because in most cases there will be more tasks than agents. Hence, agents need to schedule themselves to attempt each task in turn. Second, the tasks themselves can be very complex: requiring the agents to work on them for different lengths of time and having deadlines by when they need to be completed. The problem is complicated still further when different coalitions perform tasks with different levels of efficiency. Given all these facets, we define this as The Coalition Formation with Spatial and Temporal constraints problem (CFSTP).We show that this problem is NP-hard–in particular, it contains the wellknown complex combinatorial problem of Team Orienteering as a special case. Based on this, we design a Mixed Integer Program to optimally solve small-scale instances of the CFSTP and develop new anytime heuristics that can, on average, complete 97% of the tasks for large problems (20 agents and 300 tasks). In so doing, our solutions represent the first results for CFSTP.},
note = {Event Dates: May 2010},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The coordination of emergency responders and robots to undertake a number of tasks in disaster scenarios is a grand challenge for multi-agent systems. Central to this endeavour is the problem of forming the best teams (coalitions) of responders to perform the various tasks in the area where the disaster has struck. Moreover, these teams may have to form, disband, and reform in different areas of the disaster region. This is because in most cases there will be more tasks than agents. Hence, agents need to schedule themselves to attempt each task in turn. Second, the tasks themselves can be very complex: requiring the agents to work on them for different lengths of time and having deadlines by when they need to be completed. The problem is complicated still further when different coalitions perform tasks with different levels of efficiency. Given all these facets, we define this as The Coalition Formation with Spatial and Temporal constraints problem (CFSTP).We show that this problem is NP-hard–in particular, it contains the wellknown complex combinatorial problem of Team Orienteering as a special case. Based on this, we design a Mixed Integer Program to optimally solve small-scale instances of the CFSTP and develop new anytime heuristics that can, on average, complete 97% of the tasks for large problems (20 agents and 300 tasks). In so doing, our solutions represent the first results for CFSTP.
Ramchurn, Sarvapali; Farinelli, Alessandro; Macarthur, Kathryn; Polukarov, Mariya; Jennings, Nick
Decentralised Coordination in RoboCup Rescue Journal Article
In: The Computer Journal, vol. 53, no. 9, pp. 1–15, 2010.
@article{eps268499,
title = {Decentralised Coordination in RoboCup Rescue},
author = {Sarvapali Ramchurn and Alessandro Farinelli and Kathryn Macarthur and Mariya Polukarov and Nick Jennings},
url = {http://eprints.soton.ac.uk/268499/},
year = {2010},
date = {2010-01-01},
journal = {The Computer Journal},
volume = {53},
number = {9},
pages = {1–15},
publisher = {Oxford Journals},
abstract = {Emergency responders are faced with a number of significant challenges when managing major disasters. First, the number of rescue tasks posed is usually larger than the number of responders (or agents) and the resources available to them. Second, each task is likely to require a different level of effort in order to be completed by its deadline. Third, new tasks may continually appear or disappear from the environment, thus requiring the responders to quickly recompute their allocation of resources. Fourth, forming teams or coalitions of multiple agents from different agencies is vital since no single agency will have all the resources needed to save victims, unblock roads, and extinguish the ?res which might erupt in the disaster space. Given this, coalitions have to be efficiently selected and scheduled to work across the disaster space so as to maximise the number of lives and the portion of the infrastructure saved. In particular, it is important that the selection of such coalitions should be performed in a decentralised fashion in order to avoid a single point of failure in the system. Moreover, it is critical that responders communicate only locally given they are likely to have limited battery power or minimal access to long range communication devices. Against this background, we provide a novel decentralised solution to the coalition formation process that pervades disaster management. More specifically, we model the emergency management scenario defined in the RoboCup Rescue disaster simulation platform as a Coalition Formation with Spatial and Temporal constraints (CFST) problem where agents form coalitions in order to complete tasks, each with different demands. In order to design a decentralised algorithm for CFST we formulate it as a Distributed Constraint Optimisation problem and show how to solve it using the state-of-the-art Max-Sum algorithm that provides a completely decentralised message-passing solution. We then provide a novel algorithm (F-Max-Sum) that avoids sending redundant messages and efficiently adapts to changes in the environment. In empirical evaluations, our algorithm is shown to generate better solutions than other decentralised algorithms used for this problem.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Emergency responders are faced with a number of significant challenges when managing major disasters. First, the number of rescue tasks posed is usually larger than the number of responders (or agents) and the resources available to them. Second, each task is likely to require a different level of effort in order to be completed by its deadline. Third, new tasks may continually appear or disappear from the environment, thus requiring the responders to quickly recompute their allocation of resources. Fourth, forming teams or coalitions of multiple agents from different agencies is vital since no single agency will have all the resources needed to save victims, unblock roads, and extinguish the ?res which might erupt in the disaster space. Given this, coalitions have to be efficiently selected and scheduled to work across the disaster space so as to maximise the number of lives and the portion of the infrastructure saved. In particular, it is important that the selection of such coalitions should be performed in a decentralised fashion in order to avoid a single point of failure in the system. Moreover, it is critical that responders communicate only locally given they are likely to have limited battery power or minimal access to long range communication devices. Against this background, we provide a novel decentralised solution to the coalition formation process that pervades disaster management. More specifically, we model the emergency management scenario defined in the RoboCup Rescue disaster simulation platform as a Coalition Formation with Spatial and Temporal constraints (CFST) problem where agents form coalitions in order to complete tasks, each with different demands. In order to design a decentralised algorithm for CFST we formulate it as a Distributed Constraint Optimisation problem and show how to solve it using the state-of-the-art Max-Sum algorithm that provides a completely decentralised message-passing solution. We then provide a novel algorithm (F-Max-Sum) that avoids sending redundant messages and efficiently adapts to changes in the environment. In empirical evaluations, our algorithm is shown to generate better solutions than other decentralised algorithms used for this problem.
Vytelingum, Perukrishnen; Ramchurn, Sarvapali D.; Voice, Thomas D.; Rogers, Alex; Jennings, Nicholas R.
Trading agents for the smart electricity grid Proceedings Article
In: The Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), pp. 897–904, 2010, (Event Dates: May 10-14, 2010).
@inproceedings{eps268361,
title = {Trading agents for the smart electricity grid},
author = {Perukrishnen Vytelingum and Sarvapali D. Ramchurn and Thomas D. Voice and Alex Rogers and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/268361/},
year = {2010},
date = {2010-01-01},
booktitle = {The Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010)},
pages = {897–904},
abstract = {The vision of the Smart Grid includes the creation of intelligent electricity supply networks to allow efficient use of energy resources, reduce carbon emissions and are robust to failures. One of the key assumptions underlying this vision is that it will be possible to manage the trading of electricity between homes and micro-grids while coping with the inherent real-time dynamism in electricity demand and supply. The management of these trades needs to take into account the fact that most, if not all, of the actors in the system are self-interested and transmission line capacities are constrained. Against this background, we develop and evaluate a novel market-based mechanism and novel trading strategies for the Smart Grid. Our mechanism is based on the Continuous Double Auction (CDA) and automatically manages the congestion within the system by pricing the flow of electricity. We also introduce mechanisms to ensure the system can cope with unforeseen demand or increased supply capacity in real time. Finally, we develop new strategies that we show achieve high market efficiency (typically over 90%).},
note = {Event Dates: May 10-14, 2010},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The vision of the Smart Grid includes the creation of intelligent electricity supply networks to allow efficient use of energy resources, reduce carbon emissions and are robust to failures. One of the key assumptions underlying this vision is that it will be possible to manage the trading of electricity between homes and micro-grids while coping with the inherent real-time dynamism in electricity demand and supply. The management of these trades needs to take into account the fact that most, if not all, of the actors in the system are self-interested and transmission line capacities are constrained. Against this background, we develop and evaluate a novel market-based mechanism and novel trading strategies for the Smart Grid. Our mechanism is based on the Continuous Double Auction (CDA) and automatically manages the congestion within the system by pricing the flow of electricity. We also introduce mechanisms to ensure the system can cope with unforeseen demand or increased supply capacity in real time. Finally, we develop new strategies that we show achieve high market efficiency (typically over 90%).
Vytelingum, Perukrishnen; Voice, Thomas D.; Ramchurn, Sarvapali D.; Rogers, Alex; Jennings, Nicholas R.
Agent-Based Micro-Storage Management for the Smart Grid Proceedings Article
In: The Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010) - Won the Best Paper Award, pp. 39–46, 2010, (Winner of the Best Paper Award Event Dates: May 10-14, 2010).
@inproceedings{eps268360,
title = {Agent-Based Micro-Storage Management for the Smart Grid},
author = {Perukrishnen Vytelingum and Thomas D. Voice and Sarvapali D. Ramchurn and Alex Rogers and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/268360/},
year = {2010},
date = {2010-01-01},
booktitle = {The Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010) - Won the Best Paper Award},
pages = {39–46},
abstract = {The use of energy storage devices in homes has been advocated as one of the main ways of saving energy and reducing the reliance on fossil fuels in the future Smart Grid. However, if micro-storage devices are all charged at the same time using power from the electricity grid, it means a higher demand and, hence, more generation capacity, more carbon emissions, and, in the worst case, breaking down the system due to over-demand. To alleviate such issues, in this paper, we present a novel agent-based micro-storage management technique that allows all (individually-owned) storage devices in the system to converge to profitable, efficient behaviour. Specifically, we provide a general framework within which to analyse the Nash equilibrium of an electricity grid and devise new agent-based storage learning strategies that adapt to market conditions. Taken altogether, our solution shows that, specifically, in the UK electricity market, it is possible to achieve savings of up to 13% on average for a consumer on his electricity bill with a storage device of 4 kWh. Moreover, we show that there exists an equilibrium where only 38% of UK households would own storage devices and where social welfare would be also maximised (with an overall annual savings of nearly GBP 1.5B at that equilibrium).},
note = {Winner of the Best Paper Award Event Dates: May 10-14, 2010},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The use of energy storage devices in homes has been advocated as one of the main ways of saving energy and reducing the reliance on fossil fuels in the future Smart Grid. However, if micro-storage devices are all charged at the same time using power from the electricity grid, it means a higher demand and, hence, more generation capacity, more carbon emissions, and, in the worst case, breaking down the system due to over-demand. To alleviate such issues, in this paper, we present a novel agent-based micro-storage management technique that allows all (individually-owned) storage devices in the system to converge to profitable, efficient behaviour. Specifically, we provide a general framework within which to analyse the Nash equilibrium of an electricity grid and devise new agent-based storage learning strategies that adapt to market conditions. Taken altogether, our solution shows that, specifically, in the UK electricity market, it is possible to achieve savings of up to 13% on average for a consumer on his electricity bill with a storage device of 4 kWh. Moreover, we show that there exists an equilibrium where only 38% of UK households would own storage devices and where social welfare would be also maximised (with an overall annual savings of nearly GBP 1.5B at that equilibrium).
2009
Rahwan, Talal; Ramchurn, Sarvapali; Jennings, Nicholas; Giovannucci, Andrea
An anytime algorithm for optimal coalition structure generation Journal Article
In: Journal of Artificial Intelligence Research, vol. 34, pp. 521–567, 2009.
@article{eps267179,
title = {An anytime algorithm for optimal coalition structure generation},
author = {Talal Rahwan and Sarvapali Ramchurn and Nicholas Jennings and Andrea Giovannucci},
url = {http://eprints.soton.ac.uk/267179/},
year = {2009},
date = {2009-01-01},
journal = {Journal of Artificial Intelligence Research},
volume = {34},
pages = {521–567},
abstract = {Coalition formation is a fundamental type of interaction that involves the creation of coherent groupings of distinct, autonomous, agents in order to efficiently achieve their individual or collective goals. Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining which of the many possible coalitions to form in order to achieve some goal. This usually requires calculating a value for every possible coalition, known as the coalition value, which indicates how beneficial that coalition would be if it was formed. Once these values are calculated, the agents usually need to find a combination of coalitions, in which every agent belongs to exactly one coalition, and by which the overall outcome of the system is maximized. However, this coalition structure generation problem is extremely challenging due to the number of possible solutions that need to be examined, which grows exponentially with the number of agents involved. To date, therefore, many algorithms have been proposed to solve this problem using different techniques–ranging from dynamic programming, to integer programming, to stochastic search – all of which suffer from major limitations relating to execution time, solution quality, and memory requirements. With this in mind, we develop an anytime algorithm to solve the coalition structure generation problem. Specifically, the algorithm uses a novel representation of the search space, which partitions the space of possible solutions into sub-spaces such that it is possible to compute upper and lower bounds on the values of the best coalition structures in them. These bounds are then used to identify the sub-spaces that have no potential of containing the optimal solution so that they can be pruned. The algorithm, then, searches through the remaining sub-spaces very efficiently using a branch-and-bound technique to avoid examining all the solutions within the searched subspace(s). In this setting, we prove that our algorithm enumerates all coalition structures efficiently by avoiding redundant and invalid solutions automatically. Moreover, in order to effectively test our algorithm we develop a new type of input distribution which allows us to generate more reliable benchmarks compared to the input distributions previously used in the field. Given this new distribution, we show that for 27 agents our algorithm is able to find solutions that are optimal in 0:175% of the time required by the fastest available algorithm in the literature. The algorithm is anytime, and if interrupted before it would have normally terminated, it can still provide a solution that is guaranteed to be within a bound from the optimal one. Moreover, the guarantees we provide on the quality of the solution are significantly better than those provided by the previous state of the art algorithms designed for this purpose. For example, for the worst case distribution given 25 agents, our algorithm is able to find a 90% efficient solution in around 10% of time it takes to find the optimal solution.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Coalition formation is a fundamental type of interaction that involves the creation of coherent groupings of distinct, autonomous, agents in order to efficiently achieve their individual or collective goals. Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining which of the many possible coalitions to form in order to achieve some goal. This usually requires calculating a value for every possible coalition, known as the coalition value, which indicates how beneficial that coalition would be if it was formed. Once these values are calculated, the agents usually need to find a combination of coalitions, in which every agent belongs to exactly one coalition, and by which the overall outcome of the system is maximized. However, this coalition structure generation problem is extremely challenging due to the number of possible solutions that need to be examined, which grows exponentially with the number of agents involved. To date, therefore, many algorithms have been proposed to solve this problem using different techniques–ranging from dynamic programming, to integer programming, to stochastic search – all of which suffer from major limitations relating to execution time, solution quality, and memory requirements. With this in mind, we develop an anytime algorithm to solve the coalition structure generation problem. Specifically, the algorithm uses a novel representation of the search space, which partitions the space of possible solutions into sub-spaces such that it is possible to compute upper and lower bounds on the values of the best coalition structures in them. These bounds are then used to identify the sub-spaces that have no potential of containing the optimal solution so that they can be pruned. The algorithm, then, searches through the remaining sub-spaces very efficiently using a branch-and-bound technique to avoid examining all the solutions within the searched subspace(s). In this setting, we prove that our algorithm enumerates all coalition structures efficiently by avoiding redundant and invalid solutions automatically. Moreover, in order to effectively test our algorithm we develop a new type of input distribution which allows us to generate more reliable benchmarks compared to the input distributions previously used in the field. Given this new distribution, we show that for 27 agents our algorithm is able to find solutions that are optimal in 0:175% of the time required by the fastest available algorithm in the literature. The algorithm is anytime, and if interrupted before it would have normally terminated, it can still provide a solution that is guaranteed to be within a bound from the optimal one. Moreover, the guarantees we provide on the quality of the solution are significantly better than those provided by the previous state of the art algorithms designed for this purpose. For example, for the worst case distribution given 25 agents, our algorithm is able to find a 90% efficient solution in around 10% of time it takes to find the optimal solution.
Ramchurn, Sarvapali D.; Mezzetti, Claudio; Giovannucci, Andrea; Rodriguez, Juan A.; Dash, Rajdeep K.; Jennings, Nicholas R.
Trust-based mechanisms for robust and efficient task allocation in the presence of execution uncertainty Journal Article
In: Journal of Artificial Intelligence Research, vol. 35, pp. 1–41, 2009.
@article{eps267288,
title = {Trust-based mechanisms for robust and efficient task allocation in the presence of execution uncertainty},
author = {Sarvapali D. Ramchurn and Claudio Mezzetti and Andrea Giovannucci and Juan A. Rodriguez and Rajdeep K. Dash and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/267288/},
year = {2009},
date = {2009-01-01},
journal = {Journal of Artificial Intelligence Research},
volume = {35},
pages = {1–41},
abstract = {Vickrey-Clarke-Groves (VCG) mechanisms are often used to allocate tasks to selfish and rational agents. VCG mechanisms are incentive-compatible, direct mechanisms that are efficient (i.e. maximise social utility) and individually rational (i.e. agents prefer to join rather than opt out). However, an important assumption of these mechanisms is that the agents will always successfully complete their allocated tasks. Clearly, this assumption is unrealistic in many real-world applications where agents can, and often do, fail in their endeavours. Moreover, whether an agent is deemed to have failed may be perceived differently by different agents. Such subjective perceptions about an agent's probability of succeeding at a given task are often captured and reasoned about using the notion of trust. Given this background, in this paper we investigate the design of novel mechanisms that take into account the trust between agents when allocating tasks. Specifically, we develop a new class of mechanisms, called trust-based mechanisms, that can take into account multiple subjective measures of the probability of an agent succeeding at a given task and produce allocations that maximise social utility, whilst ensuring that no agent obtains a negative utility. We then show that such mechanisms pose a challenging new combinatorial optimisation problem (that is NP-complete), devise a novel representation for solving the problem, and develop an effective integer programming solution (that can solve instances with about 2x10^ 5 possible allocations in 40 seconds).},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Vickrey-Clarke-Groves (VCG) mechanisms are often used to allocate tasks to selfish and rational agents. VCG mechanisms are incentive-compatible, direct mechanisms that are efficient (i.e. maximise social utility) and individually rational (i.e. agents prefer to join rather than opt out). However, an important assumption of these mechanisms is that the agents will always successfully complete their allocated tasks. Clearly, this assumption is unrealistic in many real-world applications where agents can, and often do, fail in their endeavours. Moreover, whether an agent is deemed to have failed may be perceived differently by different agents. Such subjective perceptions about an agent's probability of succeeding at a given task are often captured and reasoned about using the notion of trust. Given this background, in this paper we investigate the design of novel mechanisms that take into account the trust between agents when allocating tasks. Specifically, we develop a new class of mechanisms, called trust-based mechanisms, that can take into account multiple subjective measures of the probability of an agent succeeding at a given task and produce allocations that maximise social utility, whilst ensuring that no agent obtains a negative utility. We then show that such mechanisms pose a challenging new combinatorial optimisation problem (that is NP-complete), devise a novel representation for solving the problem, and develop an effective integer programming solution (that can solve instances with about 2x10^ 5 possible allocations in 40 seconds).
Valkenhoef, Gert; Ramchurn, Sarvapali D.; Vytelingum, Perukrishnen; Jennings, Nicholas R.; Verbrugge, Rinek
Continuous double auctions with execution uncertainty Proceedings Article
In: Workshop on Trading Agent Design and Analysis (TADA-09), 2009.
@inproceedings{eps267329,
title = {Continuous double auctions with execution uncertainty},
author = {Gert Valkenhoef and Sarvapali D. Ramchurn and Perukrishnen Vytelingum and Nicholas R. Jennings and Rinek Verbrugge},
url = {http://eprints.soton.ac.uk/267329/},
year = {2009},
date = {2009-01-01},
booktitle = {Workshop on Trading Agent Design and Analysis (TADA-09)},
abstract = {We propose a novel variant of the Continuous Double Auction (CDA), the Trust-based CDA (T-CDA), which we demonstrate to be robust to execution uncertainty. This is desirable in a setting where traders may fail to deliver the goods, services or payments they have promised. Specifically, the TCDA provides a mechanism that allows agents to commit to trades they believe will maximize their expected utility. In this paper, we consider agents that use their trust in other agents to estimate the expected utility of a transaction. We empirically evaluate the mechanism, both against the optimal solution given perfect and complete information and against the standard CDA.We show that the T-CDA consistently outperforms the traditional CDA as execution uncertainty increases in the system. Furthermore, we investigate the robustness of the mechanism to unreliable trust information and find that performance degrades gracefully as information quality decreases.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We propose a novel variant of the Continuous Double Auction (CDA), the Trust-based CDA (T-CDA), which we demonstrate to be robust to execution uncertainty. This is desirable in a setting where traders may fail to deliver the goods, services or payments they have promised. Specifically, the TCDA provides a mechanism that allows agents to commit to trades they believe will maximize their expected utility. In this paper, we consider agents that use their trust in other agents to estimate the expected utility of a transaction. We empirically evaluate the mechanism, both against the optimal solution given perfect and complete information and against the standard CDA.We show that the T-CDA consistently outperforms the traditional CDA as execution uncertainty increases in the system. Furthermore, we investigate the robustness of the mechanism to unreliable trust information and find that performance degrades gracefully as information quality decreases.
2008
Adams, Niall; Field, Martin; Gelenbe, Erol; Hand, David; Jennings, Nicholas; Leslie, David; Nicholson, David; Ramchurn, Sarvapali; Rogers, Alex
Intelligent Agents for Disaster Management Proceedings Article
In: Proceedings of the IARP/EURON Workshop on Robotics for Risky Interventions and Environmental Surveillance (RISE), 2008.
@inproceedings{eps272011,
title = {Intelligent Agents for Disaster Management},
author = {Niall Adams and Martin Field and Erol Gelenbe and David Hand and Nicholas Jennings and David Leslie and David Nicholson and Sarvapali Ramchurn and Alex Rogers},
url = {http://eprints.soton.ac.uk/272011/},
year = {2008},
date = {2008-01-01},
booktitle = {Proceedings of the IARP/EURON Workshop on Robotics for Risky Interventions and Environmental Surveillance (RISE)},
abstract = {ALADDIN [1] is a multi-disciplinary project that is developing novel techniques, architectures, and mechanisms for multi-agent systems in uncertain and dynamic environments. The application focus of the project is disaster management. Research within a number of themes is being pursued and this is considering different aspects of the interaction between autonomous agents and the decentralised system architectures that support those interactions. The aim of the research is to contribute to building more robust multi-agent systems for future applications in disaster management and other similar domains.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
ALADDIN [1] is a multi-disciplinary project that is developing novel techniques, architectures, and mechanisms for multi-agent systems in uncertain and dynamic environments. The application focus of the project is disaster management. Research within a number of themes is being pursued and this is considering different aspects of the interaction between autonomous agents and the decentralised system architectures that support those interactions. The aim of the research is to contribute to building more robust multi-agent systems for future applications in disaster management and other similar domains.
Osborne, Michael A; Rogers, Alex; Ramchurn, Sarvapali; Roberts, Stephen J; Jennings, N. R.
Towards Real-Time Information Processing of Sensor Network Data using Computationally Efficient Multi-output Gaussian Processes Proceedings Article
In: International Conference on Information Processing in Sensor Networks (IPSN 2008), pp. 109–120, 2008, (Event Dates: April 2008).
@inproceedings{eps265122,
title = {Towards Real-Time Information Processing of Sensor Network Data using Computationally Efficient Multi-output Gaussian Processes},
author = {Michael A Osborne and Alex Rogers and Sarvapali Ramchurn and Stephen J Roberts and N. R. Jennings},
url = {http://eprints.soton.ac.uk/265122/},
year = {2008},
date = {2008-01-01},
booktitle = {International Conference on Information Processing in Sensor Networks (IPSN 2008)},
pages = {109–120},
abstract = {In this paper, we describe a novel, computationally efficient algorithm that facilitates the autonomous acquisition of readings from sensor networks (deciding when and which sensor to acquire readings from at any time), and which can, with minimal domain knowledge, perform a range of information processing tasks including modelling the accuracy of the sensor readings, predicting the value of missing sensor readings, and predicting how the monitored environmental variables will evolve into the future. Our motivating scenario is the need to provide situational awareness support to first responders at the scene of a large scale incident, and to this end, we describe a novel iterative formulation of a multi-output Gaussian process that can build and exploit a probabilistic model of the environmental variables being measured (including the correlations and delays that exist between them). We validate our approach using data collected from a network of weather sensors located on the south coast of England.},
note = {Event Dates: April 2008},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, we describe a novel, computationally efficient algorithm that facilitates the autonomous acquisition of readings from sensor networks (deciding when and which sensor to acquire readings from at any time), and which can, with minimal domain knowledge, perform a range of information processing tasks including modelling the accuracy of the sensor readings, predicting the value of missing sensor readings, and predicting how the monitored environmental variables will evolve into the future. Our motivating scenario is the need to provide situational awareness support to first responders at the scene of a large scale incident, and to this end, we describe a novel iterative formulation of a multi-output Gaussian process that can build and exploit a probabilistic model of the environmental variables being measured (including the correlations and delays that exist between them). We validate our approach using data collected from a network of weather sensors located on the south coast of England.
Rogers, Alex; Osborne, Michael A; Ramchurn, Sarvapali; Roberts, Stephen J; Jennings, N. R.
Information Agents for Pervasive Sensor Networks Proceedings Article
In: Sixth Annual IEEE International Conference on Pervasive Computing and Communications (PerCom 2008), pp. 294–299, 2008, (Event Dates: March 2008).
@inproceedings{eps264967,
title = {Information Agents for Pervasive Sensor Networks},
author = {Alex Rogers and Michael A Osborne and Sarvapali Ramchurn and Stephen J Roberts and N. R. Jennings},
url = {http://eprints.soton.ac.uk/264967/},
year = {2008},
date = {2008-01-01},
booktitle = {Sixth Annual IEEE International Conference on Pervasive Computing and Communications (PerCom 2008)},
pages = {294–299},
abstract = {In this paper, we describe an information agent, that resides on a mobile computer or personal digital assistant (PDA), that can autonomously acquire sensor readings from pervasive sensor networks (deciding when and which sensor to acquire readings from at any time). Moreover, it can perform a range of information processing tasks including modelling the accuracy of the sensor readings, predicting the value of missing sensor readings, and predicting how the monitored environmental parameters will evolve into the future. Our motivating scenario is the need to provide situational awareness support to first responders at the scene of a large scale incident, and we describe how we use an iterative formulation of a multi-output Gaussian process to build a probabilistic model of the environmental parameters being measured by local sensors, and the correlations and delays that exist between them. We validate our approach using data collected from a network of weather sensors located on the south coast of England.},
note = {Event Dates: March 2008},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, we describe an information agent, that resides on a mobile computer or personal digital assistant (PDA), that can autonomously acquire sensor readings from pervasive sensor networks (deciding when and which sensor to acquire readings from at any time). Moreover, it can perform a range of information processing tasks including modelling the accuracy of the sensor readings, predicting the value of missing sensor readings, and predicting how the monitored environmental parameters will evolve into the future. Our motivating scenario is the need to provide situational awareness support to first responders at the scene of a large scale incident, and we describe how we use an iterative formulation of a multi-output Gaussian process to build a probabilistic model of the environmental parameters being measured by local sensors, and the correlations and delays that exist between them. We validate our approach using data collected from a network of weather sensors located on the south coast of England.
2007
Espinoza, Fredrik; Roure, David De; Hamfors, Ola; Hinz, Lucas; Holmberg, Jesper; Jansson, Carl-Gustaf; Jennings, Nick; Luck, Mike; L"onnqvist, Peter; Ramchurn, Sarvapali; Sandin, Anna; Thompson, Mark; Bylund, Markus
Intrusiveness Management for Focused, Efficient, and Enjoyable Activities Book Section
In: The Disappearing Computer: Interaction Design, System Infrastructures and Applications for Smart Environments, pp. 143–160, Springer, 2007.
@incollection{eps265985,
title = {Intrusiveness Management for Focused, Efficient, and Enjoyable Activities},
author = {Fredrik Espinoza and David De Roure and Ola Hamfors and Lucas Hinz and Jesper Holmberg and Carl-Gustaf Jansson and Nick Jennings and Mike Luck and Peter L"onnqvist and Sarvapali Ramchurn and Anna Sandin and Mark Thompson and Markus Bylund},
url = {http://eprints.soton.ac.uk/265985/},
year = {2007},
date = {2007-01-01},
booktitle = {The Disappearing Computer: Interaction Design, System Infrastructures and Applications for Smart Environments},
pages = {143–160},
publisher = {Springer},
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Rahwan, T.; Ramchurn, S. D.; Dang, V. D.; Jennings, N. R.
Near-optimal anytime coalition structure generation Proceedings Article
In: 20th International Joint Conference on Artificial Intelligence (IJCAI), pp. 2365–2371, 2007.
@inproceedings{eps263074,
title = {Near-optimal anytime coalition structure generation},
author = {T. Rahwan and S. D. Ramchurn and V. D. Dang and N. R. Jennings},
url = {http://eprints.soton.ac.uk/263074/},
year = {2007},
date = {2007-01-01},
booktitle = {20th International Joint Conference on Artificial Intelligence (IJCAI)},
pages = {2365–2371},
abstract = {Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best set of agents that should participate in a given team. To this end, in this paper, we present a novel, anytime algorithms designed for this purpose. Our algorithm can generate solutions that either have a tight bound from the optimal or are optimal (depending on the objective) and works by partitioning the space in terms of a small set of elements that represent structures which contain coalitions of particular sizes. It then performs an online heuristic search that prunes the space and only considers valid and non-redundant coalition structures. We empirically show that we are able to find solutions that are, in the worst case, 99% efficient in 0.0043% of the time to find the optimal value by the state of the art dynamic programming (DP) algorithm (for 20 agents), using 33% less memory.},
keywords = {},
pubstate = {published},
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Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best set of agents that should participate in a given team. To this end, in this paper, we present a novel, anytime algorithms designed for this purpose. Our algorithm can generate solutions that either have a tight bound from the optimal or are optimal (depending on the objective) and works by partitioning the space in terms of a small set of elements that represent structures which contain coalitions of particular sizes. It then performs an online heuristic search that prunes the space and only considers valid and non-redundant coalition structures. We empirically show that we are able to find solutions that are, in the worst case, 99% efficient in 0.0043% of the time to find the optimal value by the state of the art dynamic programming (DP) algorithm (for 20 agents), using 33% less memory.
Rahwan, Talal; Ramchurn, Sarvapali D.; Dang, Viet D.; Giovannucci, Andrea; Jennings, N. R.
Anytime Optimal Coalition Structure Generation Proceedings Article
In: 22nd Conference on Artificial Intelligence (AAAI), pp. 1184–1190, 2007.
@inproceedings{eps263433,
title = {Anytime Optimal Coalition Structure Generation},
author = {Talal Rahwan and Sarvapali D. Ramchurn and Viet D. Dang and Andrea Giovannucci and N. R. Jennings},
url = {http://eprints.soton.ac.uk/263433/},
year = {2007},
date = {2007-01-01},
booktitle = {22nd Conference on Artificial Intelligence (AAAI)},
pages = {1184–1190},
abstract = {Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best groups of agents to select to achieve some goal. To this end, in this paper, we present a novel, optimal anytime algorithm for this coalition structure generation problem that is significantly faster than previous algorithms designed for this purpose. Specifically, our algorithm can generate solutions by partitioning the space of all potential coalitions into sub-spaces that contain coalition structures that are similar, according to some criterion, such that these sub-spaces can be pruned by identifying their bounds. Using this representation, the algorithm then searches through only valid and unique coalition structures and selects the best among them using a branch-and-bound technique. We empirically show that we are able to find solutions that are optimal in 0.082% of the time taken by the state of the art dynamic programming algorithm (for 27 agents) using much less memory (O(2^ n) instead of O(3^ n) for the set of n agents). Moreover, our algorithm is the first to be able to solve the coalition structure generation problem for numbers of agents bigger than 27 in reasonable time (less than 90 minutes for 27 agents as opposed to around 2 months for the best previous solution).},
keywords = {},
pubstate = {published},
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}
Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best groups of agents to select to achieve some goal. To this end, in this paper, we present a novel, optimal anytime algorithm for this coalition structure generation problem that is significantly faster than previous algorithms designed for this purpose. Specifically, our algorithm can generate solutions by partitioning the space of all potential coalitions into sub-spaces that contain coalition structures that are similar, according to some criterion, such that these sub-spaces can be pruned by identifying their bounds. Using this representation, the algorithm then searches through only valid and unique coalition structures and selects the best among them using a branch-and-bound technique. We empirically show that we are able to find solutions that are optimal in 0.082% of the time taken by the state of the art dynamic programming algorithm (for 27 agents) using much less memory (O(2^ n) instead of O(3^ n) for the set of n agents). Moreover, our algorithm is the first to be able to solve the coalition structure generation problem for numbers of agents bigger than 27 in reasonable time (less than 90 minutes for 27 agents as opposed to around 2 months for the best previous solution).
Ramchurn, S. D.; Sierra, C.; Godo, L.; Jennings, N. R.
Negotiating using rewards. Journal Article
In: Artificial Intelligence Journal., vol. 171, no. 10-15, pp. 805–837, 2007.
@article{eps264225,
title = {Negotiating using rewards.},
author = {S. D. Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/264225/},
year = {2007},
date = {2007-01-01},
journal = {Artificial Intelligence Journal.},
volume = {171},
number = {10-15},
pages = {805–837},
abstract = {Negotiation is a fundamental interaction mechanism in multi-agent systems because it allows self-interested agents to come to mutually beneficial agreements and partition resources efficiently and effectively. Now, in many situations, the agents need to negotiate with one another many times and so developing strategies that are effective over repeated interactions is an important challenge. Against this background, a growing body of work has examined the use of Persuasive Negotiation (PN), which involves negotiating using rhetorical arguments (such as threats, rewards, or appeals), in trying to convince an opponent to accept a given offer. Such mechanisms are especially suited to repeated encounters because they allow agents to influence the outcomes of future negotiations, while negotiating a deal in the present one, with the aim of producing results that are beneficial to both parties. To this end, in this paper, we develop a comprehensive PN mechanism for repeated interactions that makes use of rewards that can be asked for or given to. Our mechanism consists of two parts. First, a novel protocol that structures the interaction by capturing the commitments that agents incur when using rewards. Second, a new reward generation algorithm that constructs promises of rewards in future interactions as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. We then go on to develop a specific negotiation tactic, based on this reward generation algorithm, and show that it can achieve significantly better outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation in a Multi-Move Prisoners? dilemma setting, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this.},
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Negotiation is a fundamental interaction mechanism in multi-agent systems because it allows self-interested agents to come to mutually beneficial agreements and partition resources efficiently and effectively. Now, in many situations, the agents need to negotiate with one another many times and so developing strategies that are effective over repeated interactions is an important challenge. Against this background, a growing body of work has examined the use of Persuasive Negotiation (PN), which involves negotiating using rhetorical arguments (such as threats, rewards, or appeals), in trying to convince an opponent to accept a given offer. Such mechanisms are especially suited to repeated encounters because they allow agents to influence the outcomes of future negotiations, while negotiating a deal in the present one, with the aim of producing results that are beneficial to both parties. To this end, in this paper, we develop a comprehensive PN mechanism for repeated interactions that makes use of rewards that can be asked for or given to. Our mechanism consists of two parts. First, a novel protocol that structures the interaction by capturing the commitments that agents incur when using rewards. Second, a new reward generation algorithm that constructs promises of rewards in future interactions as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. We then go on to develop a specific negotiation tactic, based on this reward generation algorithm, and show that it can achieve significantly better outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation in a Multi-Move Prisoners? dilemma setting, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this.
Rogers, Alex; Dash, Rajdeep K.; Ramchurn, Sarvapali D.; Vytelingum, Perukrishnen; Jennings, N. R.
Coordinating Team Players within a Noisy Iterated Prisoner?s Dilemma Tournament Journal Article
In: Theoretical Computer Science, vol. 377, no. 1-3, pp. 243–259, 2007.
@article{eps263238,
title = {Coordinating Team Players within a Noisy Iterated Prisoner?s Dilemma Tournament},
author = {Alex Rogers and Rajdeep K. Dash and Sarvapali D. Ramchurn and Perukrishnen Vytelingum and N. R. Jennings},
url = {http://eprints.soton.ac.uk/263238/},
year = {2007},
date = {2007-01-01},
journal = {Theoretical Computer Science},
volume = {377},
number = {1-3},
pages = {243–259},
abstract = {In this paper, we present our investigation into the use of a team of players within a noisy Iterated Prisoner?s Dilemma (IPD) tournament. We show that the members of such a team are able to use a pre-arranged sequence of moves that they make at the start of each interaction in order to recognise one another, and that by coordinating their actions they can increase the chances that one of the team members wins the round-robin style tournament. We consider, in detail, the factors that influence the performance of this team and we show that the problem that the team members face, when they attempt to recognise one another within the noisy IPD tournament, is exactly analogous to the problem, studied in information theory, of communicating reliably over a noisy channel. Thus we demonstrate that we can use error correcting codes to implement this recognition, and by doing so, further optimise the performance of the team.},
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In this paper, we present our investigation into the use of a team of players within a noisy Iterated Prisoner?s Dilemma (IPD) tournament. We show that the members of such a team are able to use a pre-arranged sequence of moves that they make at the start of each interaction in order to recognise one another, and that by coordinating their actions they can increase the chances that one of the team members wins the round-robin style tournament. We consider, in detail, the factors that influence the performance of this team and we show that the problem that the team members face, when they attempt to recognise one another within the noisy IPD tournament, is exactly analogous to the problem, studied in information theory, of communicating reliably over a noisy channel. Thus we demonstrate that we can use error correcting codes to implement this recognition, and by doing so, further optimise the performance of the team.
Rogers, Alex; Dash, Rajdeep K.; Ramchurn, Sarvapali D.; Vytelingum, Perukrishnen; Jennings, N. R.
Error-Correcting Codes for Team Coordination within a Noisy Iterated Prisoner?s Dilemma Tournament Book Section
In: Kendel, Graham; Yao, Xin; Chong, Siang Yew (Ed.): The Iterated Prisoners Dilemma Competition: Celebrating the 20th Anniversary, pp. 205–229, World Scientific, 2007.
@incollection{eps263264,
title = {Error-Correcting Codes for Team Coordination within a Noisy Iterated Prisoner?s Dilemma Tournament},
author = {Alex Rogers and Rajdeep K. Dash and Sarvapali D. Ramchurn and Perukrishnen Vytelingum and N. R. Jennings},
editor = {Graham Kendel and Xin Yao and Siang Yew Chong},
url = {http://eprints.soton.ac.uk/263264/},
year = {2007},
date = {2007-01-01},
booktitle = {The Iterated Prisoners Dilemma Competition: Celebrating the 20th Anniversary},
pages = {205–229},
publisher = {World Scientific},
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2006
Karunatillake, N. C.; Jennings, N. R.; Rahwan, I.; Ramchurn, S. D.
Managing Social Influences through Argumentation-Based Negotiation Proceedings Article
In: Third International Workshop on Argumentation in Multi-Agent Systems (ArgMAS 2006), pp. 35–52, 2006, (Event Dates: 8th May 2006).
@inproceedings{eps262022,
title = {Managing Social Influences through Argumentation-Based Negotiation},
author = {N. C. Karunatillake and N. R. Jennings and I. Rahwan and S. D. Ramchurn},
url = {http://eprints.soton.ac.uk/262022/},
year = {2006},
date = {2006-01-01},
booktitle = {Third International Workshop on Argumentation in Multi-Agent Systems (ArgMAS 2006)},
pages = {35–52},
abstract = {Social influences play an important part in the actions that an individual agent may perform within a multi-agent society. However, the incomplete knowledge and the diverse and conflicting influences present within such societies, may stop an agent from abiding by all its social influences. This may, in turn, lead to conflicts that the agents need to identify, manage, and resolve in order for the society to behave in a coherent manner. To this end, we present an empirical study of an argumentation-based negotiation (ABN) approach that allows the agents to detect such conflicts, and then manage and resolve them through the use of argumentative dialogues. To test our theory, we map our ABN model to a multi-agent task allocation scenario. Our results show that using an argumentation approach allows agents to both efficiently and effectively manage their social influences even under high degrees of incompleteness. Finally, we show that allowing agents to argue and resolve such conflicts early in the negotiation encounter increases their efficiency in managing social influences.},
note = {Event Dates: 8th May 2006},
keywords = {},
pubstate = {published},
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}
Social influences play an important part in the actions that an individual agent may perform within a multi-agent society. However, the incomplete knowledge and the diverse and conflicting influences present within such societies, may stop an agent from abiding by all its social influences. This may, in turn, lead to conflicts that the agents need to identify, manage, and resolve in order for the society to behave in a coherent manner. To this end, we present an empirical study of an argumentation-based negotiation (ABN) approach that allows the agents to detect such conflicts, and then manage and resolve them through the use of argumentative dialogues. To test our theory, we map our ABN model to a multi-agent task allocation scenario. Our results show that using an argumentation approach allows agents to both efficiently and effectively manage their social influences even under high degrees of incompleteness. Finally, we show that allowing agents to argue and resolve such conflicts early in the negotiation encounter increases their efficiency in managing social influences.
Ramchurn, S. D.; Sierra, C.; Godo, L.; Jennings, N. R.
Negotiating using rewards Proceedings Article
In: 5th Int. Conf. on Autonomous Agents and Multi-Agent Systems, pp. 400–407, 2006.
@inproceedings{eps262591,
title = {Negotiating using rewards},
author = {S. D. Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/262591/},
year = {2006},
date = {2006-01-01},
booktitle = {5th Int. Conf. on Autonomous Agents and Multi-Agent Systems},
journal = {Proc. 5th Int. Conf. on Autonomous Agents and Multi-Agent Systems, Hakodate, Japan},
pages = {400–407},
abstract = {In situations where self-interested agents interact repeatedly, it is important that they are endowed with negotiation techniques that enable them to reach agreements that are profitable in the long run. To this end, we devise a novel negotiation algorithm that generates promises of rewards in future interactions, as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. Moreover, we thus develop a specific negotiation tactic based on this reward generation algorithm and show that it can achieve significantly bettter outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this under concrete settings.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In situations where self-interested agents interact repeatedly, it is important that they are endowed with negotiation techniques that enable them to reach agreements that are profitable in the long run. To this end, we devise a novel negotiation algorithm that generates promises of rewards in future interactions, as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. Moreover, we thus develop a specific negotiation tactic based on this reward generation algorithm and show that it can achieve significantly bettter outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this under concrete settings.
2005
Ashri, R.; Ramchurn, S. D.; Sabater, J.; Luck, M.; Jennings, N. R.
Trust evaluation through relationship analysis Proceedings Article
In: 4th Int Joint Conf. on Autonomous Agents and Multi-Agent Systems, pp. 1005–1011, 2005.
@inproceedings{eps260806,
title = {Trust evaluation through relationship analysis},
author = {R. Ashri and S. D. Ramchurn and J. Sabater and M. Luck and N. R. Jennings},
url = {http://eprints.soton.ac.uk/260806/},
year = {2005},
date = {2005-01-01},
booktitle = {4th Int Joint Conf. on Autonomous Agents and Multi-Agent Systems},
journal = {Proceedings: 4th International Joint Conference on Autonomous Agents and Multi-Agent Systems},
pages = {1005–1011},
abstract = {Current mechanisms for evaluating the trustworthiness of an agent within an electronic marketplace depend either on using a history of interactions or on recommendations from other agents. In the first case, these requirements limit what an agent with no prior interaction history can do. In the second case, they transform the problem into one of trusting the recommending agent. However, these mechanisms do not consider the relationships between agents that arise through interactions (such as buying or selling) or through overarching organisational structures (such as hierarchical or flat), which can also aid in evaluating trustworthiness. In response, this paper outlines a method that enables agents to evaluate the trustworthiness of their counterparts, based solely on an analysis of such relationships. Specifically, relationships are identified using a generic technique in conjunction with a basic model for agentbased marketplaces. They are then interpreted through a trust model that enables the inference of trust valuations based on the different types of relationships. In this way, we provide a further component for a trust evaluation model that addresses some of the limitations of existing work.},
keywords = {},
pubstate = {published},
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}
Current mechanisms for evaluating the trustworthiness of an agent within an electronic marketplace depend either on using a history of interactions or on recommendations from other agents. In the first case, these requirements limit what an agent with no prior interaction history can do. In the second case, they transform the problem into one of trusting the recommending agent. However, these mechanisms do not consider the relationships between agents that arise through interactions (such as buying or selling) or through overarching organisational structures (such as hierarchical or flat), which can also aid in evaluating trustworthiness. In response, this paper outlines a method that enables agents to evaluate the trustworthiness of their counterparts, based solely on an analysis of such relationships. Specifically, relationships are identified using a generic technique in conjunction with a basic model for agentbased marketplaces. They are then interpreted through a trust model that enables the inference of trust valuations based on the different types of relationships. In this way, we provide a further component for a trust evaluation model that addresses some of the limitations of existing work.
Blankenburg, B.; Dash, R. K.; Ramchurn, S. D.; Klusch, M.; Jennings, N. R.
Trusted kernel-based coalition formation Proceedings Article
In: Proc. 4th Int Joint Conf on Autonomous Agents and Multi-Agent Systems, pp. 989–996, 2005.
@inproceedings{eps260808,
title = {Trusted kernel-based coalition formation},
author = {B. Blankenburg and R. K. Dash and S. D. Ramchurn and M. Klusch and N. R. Jennings},
url = {http://eprints.soton.ac.uk/260808/},
year = {2005},
date = {2005-01-01},
booktitle = {Proc. 4th Int Joint Conf on Autonomous Agents and Multi-Agent Systems},
journal = {Proceedings: 4th International Joint Conference on Autonomous Agents and Multi-agent Systems},
pages = {989–996},
abstract = {We define Trusted Kernel-based Coalition Formation as a novel extension to the traditional kernel-based coalition formation process which ensures agents choose the most reliable coalition partners and are guaranteed to obtain the payment they deserve. To this end, we develop an encryption-based communication protocol and a payment scheme which ensure that agents cannot manipulate the mechanism to their own benefit. Moreover, we integrate a generic trust model in the coalition formation process that permits the selection of the most reliable agents over repeated coalition games. We empirically evaluate our mechanism when iterated and show that, in the long run, it always chooses the coalition structure that has the maximum expected value and determines the payoffs that match their level of reliability.},
keywords = {},
pubstate = {published},
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We define Trusted Kernel-based Coalition Formation as a novel extension to the traditional kernel-based coalition formation process which ensures agents choose the most reliable coalition partners and are guaranteed to obtain the payment they deserve. To this end, we develop an encryption-based communication protocol and a payment scheme which ensure that agents cannot manipulate the mechanism to their own benefit. Moreover, we integrate a generic trust model in the coalition formation process that permits the selection of the most reliable agents over repeated coalition games. We empirically evaluate our mechanism when iterated and show that, in the long run, it always chooses the coalition structure that has the maximum expected value and determines the payoffs that match their level of reliability.
Ramchurn, S. D.; Jennings, N. R.
Trust in agent-based software Book Section
In: Mansell, R.; Collins, B. S. (Ed.): Trust and Crime in Information Societies, pp. 165–204, Elgar Publishing, 2005.
@incollection{eps260823,
title = {Trust in agent-based software},
author = {S. D. Ramchurn and N. R. Jennings},
editor = {R. Mansell and B. S. Collins},
url = {http://eprints.soton.ac.uk/260823/},
year = {2005},
date = {2005-01-01},
booktitle = {Trust and Crime in Information Societies},
pages = {165–204},
publisher = {Elgar Publishing},
keywords = {},
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2004
Dash, R. K.; Ramchurn, S. D.; Jennings, N. R.
Trust-Based Mechanism Design Proceedings Article
In: 3rd Int. Conf. on Autonomous Agents and Multi-Agent Systems, pp. 748–755, 2004, (Event Dates: 19-23 July 2004).
@inproceedings{eps259352,
title = {Trust-Based Mechanism Design},
author = {R. K. Dash and S. D. Ramchurn and N. R. Jennings},
url = {http://eprints.soton.ac.uk/259352/},
year = {2004},
date = {2004-01-01},
booktitle = {3rd Int. Conf. on Autonomous Agents and Multi-Agent Systems},
pages = {748–755},
abstract = {We define trust-based mechanism design as an augmentation of traditional mechanism design in which agents take into account the degree of trust that they have in their counterparts when determining their allocations. To this end, we develop an efficient, individually rational, and incentive compatible mechanism based on trust. This mechanism is embedded in a task allocation scenario in which the trust in an agent is derived from the reported performance success of that agent by all the other agents in the system. We also empirically study the evolution of our mechanism when iterated and show that, in the long run, it always chooses the most successful and cheapest agents to fulfill an allocation and chooses better allocations than other comparable models when faced with biased reporting.},
note = {Event Dates: 19-23 July 2004},
keywords = {},
pubstate = {published},
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}
We define trust-based mechanism design as an augmentation of traditional mechanism design in which agents take into account the degree of trust that they have in their counterparts when determining their allocations. To this end, we develop an efficient, individually rational, and incentive compatible mechanism based on trust. This mechanism is embedded in a task allocation scenario in which the trust in an agent is derived from the reported performance success of that agent by all the other agents in the system. We also empirically study the evolution of our mechanism when iterated and show that, in the long run, it always chooses the most successful and cheapest agents to fulfill an allocation and chooses better allocations than other comparable models when faced with biased reporting.
Ramchurn, S. D.; Deitch, B.; Thompson, M. K.; Roure, D. C.; Jennings, N. R.; Luck, M.
Minimising intrusiveness in pervasive computing environments using multi-agent negotiation Proceedings Article
In: First Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous'04), pp. 364–372, IEEE, 2004, (Event Dates: August 22 - 26, 2004).
@inproceedings{eps259566,
title = {Minimising intrusiveness in pervasive computing environments using multi-agent negotiation},
author = {S. D. Ramchurn and B. Deitch and M. K. Thompson and D. C. Roure and N. R. Jennings and M. Luck},
url = {http://eprints.soton.ac.uk/259566/},
year = {2004},
date = {2004-01-01},
booktitle = {First Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous'04)},
pages = {364–372},
publisher = {IEEE},
abstract = {This paper highlights intrusiveness as a key issue in the field of pervasive computing environments and presents a multi-agent approach to tackling it. Specifically, we discuss how interruptions can impact on individual and group tasks and how they can be managed by taking into account user and group preferences through negotiation between software agents. The system we develop is implemented on the Jabber platform and is deployed in the context of a meeting room scenario.},
note = {Event Dates: August 22 - 26, 2004},
keywords = {},
pubstate = {published},
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}
This paper highlights intrusiveness as a key issue in the field of pervasive computing environments and presents a multi-agent approach to tackling it. Specifically, we discuss how interruptions can impact on individual and group tasks and how they can be managed by taking into account user and group preferences through negotiation between software agents. The system we develop is implemented on the Jabber platform and is deployed in the context of a meeting room scenario.
Ramchurn, S. D.; Huynh, T. D.; Jennings, N. R.
Trust in Multiagent Systems Journal Article
In: The Knowledge Engineering Review, vol. 19, no. 1, pp. 1–25, 2004.
@article{eps259564,
title = {Trust in Multiagent Systems},
author = {S. D. Ramchurn and T. D. Huynh and N. R. Jennings},
url = {http://eprints.soton.ac.uk/259564/},
year = {2004},
date = {2004-01-01},
journal = {The Knowledge Engineering Review},
volume = {19},
number = {1},
pages = {1–25},
abstract = {Trust is a fundamental concern in large-scale open distributed systems. It lies at the core of all interactions between the entities that have to operate in such uncertain and constantly changing environments. Given this complexity, these components, and the ensuing system, are increasingly being conceptualised, designed, and built using agent-based techniques and, to this end, this paper examines the specific role of trust in multi-agent systems. In particular, we survey the state of the art and provide an account of the main directions along which research efforts are being focused. In so doing, we critically evaluate the relative strengths and weaknesses of the main models that have been proposed and show how, fundamentally, they all seek to minimise the uncertainty in interactions. Finally, we outline the areas that require further research in order to develop a comprehensive treatment of trust in complex computational settings.},
keywords = {},
pubstate = {published},
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Trust is a fundamental concern in large-scale open distributed systems. It lies at the core of all interactions between the entities that have to operate in such uncertain and constantly changing environments. Given this complexity, these components, and the ensuing system, are increasingly being conceptualised, designed, and built using agent-based techniques and, to this end, this paper examines the specific role of trust in multi-agent systems. In particular, we survey the state of the art and provide an account of the main directions along which research efforts are being focused. In so doing, we critically evaluate the relative strengths and weaknesses of the main models that have been proposed and show how, fundamentally, they all seek to minimise the uncertainty in interactions. Finally, we outline the areas that require further research in order to develop a comprehensive treatment of trust in complex computational settings.
Ramchurn, Sarvapali
Multi-Agent Negotiation using Trust and Persuasion PhD Thesis
University of Southampton, 2004.
@phdthesis{eps260200,
title = {Multi-Agent Negotiation using Trust and Persuasion},
author = {Sarvapali Ramchurn},
url = {http://eprints.soton.ac.uk/260200/},
year = {2004},
date = {2004-01-01},
school = {University of Southampton},
abstract = {In this thesis, we propose a panoply of tools and techniques to manage inter-agent dependencies in open, distributed multi-agent systems that have significant degrees of uncertainty. In particular, we focus on situations in which agents are involved in repeated interactions where they need to negotiate to resolve conflicts that may arise between them. To this end, we endow agents with decision making models that exploit the notion of trust and use persuasive techniques during the negotiation process to reduce the level of uncertainty and achieve better deals in the long run. Firstly, we develop and evaluate a new trust model (called CREDIT) that allows agents to measure the degree of trust they should place in their opponents. This model reduces the uncertainty that agents have about their opponents' reliability. Thus, over repeated interactions, CREDIT enables agents to model their opponents' reliability using probabilistic techniques and a fuzzy reasoning mechanism that allows the combination of measures based on reputation (indirect interactions) and confidence (direct interactions). In so doing, CREDIT takes a wider range of behaviour-influencing factors into account than existing models, including the norms of the agents and the institution within which transactions occur. We then explore a novel application of trust models by showing how the measures developed in CREDIT ca be applied negotiations in multiple encounters. Specifically we show that agents that use CREDIT are able to avoid unreliable agents, both during the selection of interaction partners and during the negotiation process itself by using trust to adjust their negotiation stance. Also, we empirically show that agents are able to reach good deals with agents that are unreliable to some degree (rather than completely unreliable) and with those that try to strategically exploit their opponent. Secondly, having applied CREDIT to negotiations, we further extend the application of trust to reduce uncertainty about the reliability of agents in mechanism design (where the honesty of agents is elicited by the protocol). Thus, we develop $backslash$acftbmd that allows agents using a trust model (such as CREDIT) to reach efficient agreements that choose the most reliable agents in the long run. In particular, we show that our mechanism enforces truth-telling from the agents (i.e. it is incentive compatible), both about their perceived reliability of their opponent and their valuations for the goods to be traded. In proving the latter properties, our trust-based mechanism is shown to be the first reputation mechanism that implements individual rationality, incentive compatibility, and efficiency. Our trust-based mechanism is also empirically evaluated and shown to be better than other comparable models in reaching the outcome that maximises all the negotiating agents' utilities and in choosing the most reliable agents in the long run. Thirdly, having explored ways to reduce uncertainties about reliability and honesty, we use persuasive negotiation techniques to tackle issues associated with uncertainties that agents have about the preferences and the space of possible agreements. To this end, we propose a novel protocol and reasoning mechanism that agents can use to generate and evaluate persuasive elements, such as promises of future rewards, to support the offers they make during negotiation. These persuasive elements aim to make offers more attractive over multiple encounters given the absence of information about an opponent's discount factors or exact payoffs. Specifically, we empirically demonstrate that agents are able to achieve a larger number of agreements and a higher expected utility over repeated encounters when they are given the capability to give or ask for rewards. Moreover, we develop a novel strategy using this protocol and show that it outperforms existing state of the art heuristic negotiation models. Finally, the applicability of persuasive negotiation and CREDIT is exemplified through a practical implementation in a pervasive computing environment. In this context, the negotiation mechanism is implemented in an instant messaging platform (JABBER) and used to resolve conflicts between group and individual preferences that arise in a meeting room scenario. In particular, we show how persuasive negotiation and trust permit a flexible management of interruptions by allowing intrusions to happen at appropriate times during the meeting while still managing to satisfy the preferences of all parties present.},
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In this thesis, we propose a panoply of tools and techniques to manage inter-agent dependencies in open, distributed multi-agent systems that have significant degrees of uncertainty. In particular, we focus on situations in which agents are involved in repeated interactions where they need to negotiate to resolve conflicts that may arise between them. To this end, we endow agents with decision making models that exploit the notion of trust and use persuasive techniques during the negotiation process to reduce the level of uncertainty and achieve better deals in the long run. Firstly, we develop and evaluate a new trust model (called CREDIT) that allows agents to measure the degree of trust they should place in their opponents. This model reduces the uncertainty that agents have about their opponents' reliability. Thus, over repeated interactions, CREDIT enables agents to model their opponents' reliability using probabilistic techniques and a fuzzy reasoning mechanism that allows the combination of measures based on reputation (indirect interactions) and confidence (direct interactions). In so doing, CREDIT takes a wider range of behaviour-influencing factors into account than existing models, including the norms of the agents and the institution within which transactions occur. We then explore a novel application of trust models by showing how the measures developed in CREDIT ca be applied negotiations in multiple encounters. Specifically we show that agents that use CREDIT are able to avoid unreliable agents, both during the selection of interaction partners and during the negotiation process itself by using trust to adjust their negotiation stance. Also, we empirically show that agents are able to reach good deals with agents that are unreliable to some degree (rather than completely unreliable) and with those that try to strategically exploit their opponent. Secondly, having applied CREDIT to negotiations, we further extend the application of trust to reduce uncertainty about the reliability of agents in mechanism design (where the honesty of agents is elicited by the protocol). Thus, we develop $backslash$acftbmd that allows agents using a trust model (such as CREDIT) to reach efficient agreements that choose the most reliable agents in the long run. In particular, we show that our mechanism enforces truth-telling from the agents (i.e. it is incentive compatible), both about their perceived reliability of their opponent and their valuations for the goods to be traded. In proving the latter properties, our trust-based mechanism is shown to be the first reputation mechanism that implements individual rationality, incentive compatibility, and efficiency. Our trust-based mechanism is also empirically evaluated and shown to be better than other comparable models in reaching the outcome that maximises all the negotiating agents' utilities and in choosing the most reliable agents in the long run. Thirdly, having explored ways to reduce uncertainties about reliability and honesty, we use persuasive negotiation techniques to tackle issues associated with uncertainties that agents have about the preferences and the space of possible agreements. To this end, we propose a novel protocol and reasoning mechanism that agents can use to generate and evaluate persuasive elements, such as promises of future rewards, to support the offers they make during negotiation. These persuasive elements aim to make offers more attractive over multiple encounters given the absence of information about an opponent's discount factors or exact payoffs. Specifically, we empirically demonstrate that agents are able to achieve a larger number of agreements and a higher expected utility over repeated encounters when they are given the capability to give or ask for rewards. Moreover, we develop a novel strategy using this protocol and show that it outperforms existing state of the art heuristic negotiation models. Finally, the applicability of persuasive negotiation and CREDIT is exemplified through a practical implementation in a pervasive computing environment. In this context, the negotiation mechanism is implemented in an instant messaging platform (JABBER) and used to resolve conflicts between group and individual preferences that arise in a meeting room scenario. In particular, we show how persuasive negotiation and trust permit a flexible management of interruptions by allowing intrusions to happen at appropriate times during the meeting while still managing to satisfy the preferences of all parties present.
Ramchurn, Sarvapali; Sierra, C.; Godo, L.; Jennings, N. R.
Devising a trust model for multi-agent interactions using confidence and reputation Journal Article
In: International Journal of Applied Artificial Intelligence, vol. 18, no. 9-10, pp. 833–852, 2004.
@article{eps260155,
title = {Devising a trust model for multi-agent interactions using confidence and reputation},
author = {Sarvapali Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
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year = {2004},
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2003
Rahwan, I.; Ramchurn, Sarvapali; Jennings, N. R.; McBurney, P.; Parsons, S.; Sonenberg, L.
Argumentation-based negotiation Journal Article
In: The Knowledge Engineering Review, vol. 18, no. 4, pp. 343–375, 2003.
@article{eps258850,
title = {Argumentation-based negotiation},
author = {I. Rahwan and Sarvapali Ramchurn and N. R. Jennings and P. McBurney and S. Parsons and L. Sonenberg},
url = {http://eprints.soton.ac.uk/258850/},
year = {2003},
date = {2003-01-01},
journal = {The Knowledge Engineering Review},
volume = {18},
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abstract = {Negotiation is essential in settings where autonomous agents have con- flicting interests and a desire to cooperate. For this reason, mechanisms in which agents exchange potential agreements according to various rules of interaction have become very popular in recent years as evident, for example, in the auction and mechanism design community. However, a growing body of research is now emerging which points out limitations in such mechanisms and advocates the idea that agents can increase the likelihood and quality of an agreement by exchanging arguments which in- fluence each others? states. This community further argues that argument exchange is sometimes essential when various assumptions about agent rationality cannot be satisfied. To this end, in this article, we identify the main research motivations and ambitions behind work in the field. We then provide a conceptual framework through which we outline the core elements and features required by agents engaged in argumentation-based negotiation, as well as the environment that hosts these agents. For each of these elements, we survey and evaluate existing proposed techniques in the literature and highlight the major challenges that need to be addressed if argument-based negotiation research is to reach its full potential.},
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Negotiation is essential in settings where autonomous agents have con- flicting interests and a desire to cooperate. For this reason, mechanisms in which agents exchange potential agreements according to various rules of interaction have become very popular in recent years as evident, for example, in the auction and mechanism design community. However, a growing body of research is now emerging which points out limitations in such mechanisms and advocates the idea that agents can increase the likelihood and quality of an agreement by exchanging arguments which in- fluence each others? states. This community further argues that argument exchange is sometimes essential when various assumptions about agent rationality cannot be satisfied. To this end, in this article, we identify the main research motivations and ambitions behind work in the field. We then provide a conceptual framework through which we outline the core elements and features required by agents engaged in argumentation-based negotiation, as well as the environment that hosts these agents. For each of these elements, we survey and evaluate existing proposed techniques in the literature and highlight the major challenges that need to be addressed if argument-based negotiation research is to reach its full potential.
Ramchurn, S. D.; Jennings, N. R.; Sierra, C.
Persuasive negotiation for autonomous agents: A rhetorical approach Proceedings Article
In: IJCAI Workshop on Computational Models of Natural Argument, pp. 9–17, 2003.
@inproceedings{eps258541,
title = {Persuasive negotiation for autonomous agents: A rhetorical approach},
author = {S. D. Ramchurn and N. R. Jennings and C. Sierra},
url = {http://eprints.soton.ac.uk/258541/},
year = {2003},
date = {2003-01-01},
booktitle = {IJCAI Workshop on Computational Models of Natural Argument},
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abstract = {Persuasive negotiation occurs when autonomous agents exchange proposals that are backed up by rhetorical arguments (such as threats, rewards, or appeals). The role of such rhetorical arguments is to persuade the negotiation opponent to accept proposals more readily. To this end, this paper presents a rhetorical model of persuasion that defines the main types of rhetorical particles that are used and that provides a decision making model to enable an agent to determine what type of rhetorical argument to send in a given context and how to evaluate rhetorical arguments that are received. The model is empirically evaluated and we show that it is effective and efficient in reaching agreements.},
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Persuasive negotiation occurs when autonomous agents exchange proposals that are backed up by rhetorical arguments (such as threats, rewards, or appeals). The role of such rhetorical arguments is to persuade the negotiation opponent to accept proposals more readily. To this end, this paper presents a rhetorical model of persuasion that defines the main types of rhetorical particles that are used and that provides a decision making model to enable an agent to determine what type of rhetorical argument to send in a given context and how to evaluate rhetorical arguments that are received. The model is empirically evaluated and we show that it is effective and efficient in reaching agreements.
Ramchurn, Sarvapali; Sierra, C.; Godo, L.; Jennings, N. R.
A computational trust model for multi-agent interactions based on confidence and reputation Proceedings Article
In: 6th International Workshop of Deception, Fraud and Trust in Agent Societies, pp. 69–75, 2003, (Event Dates: 2003).
@inproceedings{eps258542,
title = {A computational trust model for multi-agent interactions based on confidence and reputation},
author = {Sarvapali Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/258542/},
year = {2003},
date = {2003-01-01},
booktitle = {6th International Workshop of Deception, Fraud and Trust in Agent Societies},
pages = {69–75},
abstract = {In open environments in which autonomous agents can break contracts, computational models of trust have an important role to play in determining who to interact with and how interactions unfold. To this end, we develop such a trust model, based on confi- dence and reputation, and show how it can be concretely applied, using fuzzy sets, to guide agents in evaluating past interactions and in establishing new contracts with one another.},
note = {Event Dates: 2003},
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In open environments in which autonomous agents can break contracts, computational models of trust have an important role to play in determining who to interact with and how interactions unfold. To this end, we develop such a trust model, based on confi- dence and reputation, and show how it can be concretely applied, using fuzzy sets, to guide agents in evaluating past interactions and in establishing new contracts with one another.
2002
Panzarasa, P.; Ramchurn, S. D.; Jennings, Nick
Intrusiveness, Trust and Argumentation: Using Automated Negotiation to Inhibit the Transmission of Disruptive Information Proceedings Article
In: Proceedings of the International Conference on Computational Social and Organizational Systems, 2002.
@inproceedings{eps272014,
title = {Intrusiveness, Trust and Argumentation: Using Automated Negotiation to Inhibit the Transmission of Disruptive Information},
author = {P. Panzarasa and S. D. Ramchurn and Nick Jennings},
url = {http://eprints.soton.ac.uk/272014/},
year = {2002},
date = {2002-01-01},
booktitle = {Proceedings of the International Conference on Computational Social and Organizational Systems},
abstract = {The question of how to promote the growth and diffusion of information has been extensively addressed by a wide research community. A common assumption underpinning most studies is that the information to be transmitted is useful and of high quality. In this paper, we endorse a complementary perspective. We investigate how the growth and diffusion of high quality information can be managed and maximized by preventing, dampening and minimizing the diffusion of low quality, unwanted information. To this end, we focus on the conflict between pervasive computing environments and the joint activities undertaken in parallel local social contexts. When technologies for distributed activities (e.g. mobile technology) develop, both artifacts and services that enable people to participate in non-local contexts are likely to intrude on local situations. As a mechanism for minimizing the intrusion of the technology, we develop a computational model of argumentation-based negotiation among autonomous agents. A key component in the model is played by trust: what arguments are used and how they are evaluated depend on how trustworthy the agents judge one another. To gain an insight into the implications of the model, we conduct a number of virtual experiments. Results enable us to explore how intrusiveness is affected by trust, the negotiation network and the agents' abilities of conducting argumentation.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The question of how to promote the growth and diffusion of information has been extensively addressed by a wide research community. A common assumption underpinning most studies is that the information to be transmitted is useful and of high quality. In this paper, we endorse a complementary perspective. We investigate how the growth and diffusion of high quality information can be managed and maximized by preventing, dampening and minimizing the diffusion of low quality, unwanted information. To this end, we focus on the conflict between pervasive computing environments and the joint activities undertaken in parallel local social contexts. When technologies for distributed activities (e.g. mobile technology) develop, both artifacts and services that enable people to participate in non-local contexts are likely to intrude on local situations. As a mechanism for minimizing the intrusion of the technology, we develop a computational model of argumentation-based negotiation among autonomous agents. A key component in the model is played by trust: what arguments are used and how they are evaluated depend on how trustworthy the agents judge one another. To gain an insight into the implications of the model, we conduct a number of virtual experiments. Results enable us to explore how intrusiveness is affected by trust, the negotiation network and the agents' abilities of conducting argumentation.