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121.
Chen, S.; Wu, F.; Shen, L.; Chen, J.; Ramchurn, S. D.
Decentralized Patrolling Under Constraints in Dynamic Environments Journal Article
In: Cybernetics, IEEE Transactions on, vol. PP, no. 99, pp. 1-13, 2015, ISSN: 2168-2267.
@article{7362160,
title = {Decentralized Patrolling Under Constraints in Dynamic Environments},
author = {S. Chen and F. Wu and L. Shen and J. Chen and S. D. Ramchurn},
doi = {10.1109/TCYB.2015.2505737},
issn = {2168-2267},
year = {2015},
date = {2015-01-01},
journal = {Cybernetics, IEEE Transactions on},
volume = {PP},
number = {99},
pages = {1-13},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
122.
Kalyanaraman, Shivkumar; Seetharam, Deva P; Shorey, Rajeev; Ramchurn, Sarvapali D; Srivastava, Mani (Ed.)
ACM, 2015, ISBN: 978-1-4503-3609-3.
@proceedings{DBLP:conf/eenergy/2015,
title = {Proceedings of the 2015 ACM Sixth International Conference on Future
Energy Systems, e-Energy 2015, Bangalore, India, July 14-17, 2015},
editor = {Shivkumar Kalyanaraman and Deva P Seetharam and Rajeev Shorey and Sarvapali D Ramchurn and Mani Srivastava},
url = {http://dl.acm.org/citation.cfm?id=2768510},
isbn = {978-1-4503-3609-3},
year = {2015},
date = {2015-01-01},
publisher = {ACM},
keywords = {},
pubstate = {published},
tppubtype = {proceedings}
}
123.
Bicego, A. Farinelli F. Recchia M.
Behavioural biometrics using electricity load profiles Journal Article
In: Proceedings of the International Conference on Pattern Recognition, 2014.
@article{bicego:etal:2014,
title = {Behavioural biometrics using electricity load profiles},
author = {A. Farinelli F. Recchia M. Bicego},
url = {https://www.sramchurn.com/wp-content/uploads/2014/10/CR_v1.pdf},
year = {2014},
date = {2014-08-24},
journal = {Proceedings of the International Conference on Pattern Recognition},
abstract = {Modelling behavioural biometric patterns is a key
issue for modern user centric applications, aimed at better monitoring
users’ activities, understanding their habits and detecting
their identity. Following this trend, this paper investigates whether
the electrical energy consumption of a user can be a distinctive
behavioural biometric trait. In particular we analyse daily and
weekly load profiles showing that they are closely related to
the identity of the users. Hence, we believe that this level of
analysis can open interesting application scenarios in the field of
energy management and it provides a good working framework
for the continuous development of smart environments with
demonstrable benefits on real-world implementations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Modelling behavioural biometric patterns is a key
issue for modern user centric applications, aimed at better monitoring
users’ activities, understanding their habits and detecting
their identity. Following this trend, this paper investigates whether
the electrical energy consumption of a user can be a distinctive
behavioural biometric trait. In particular we analyse daily and
weekly load profiles showing that they are closely related to
the identity of the users. Hence, we believe that this level of
analysis can open interesting application scenarios in the field of
energy management and it provides a good working framework
for the continuous development of smart environments with
demonstrable benefits on real-world implementations.
issue for modern user centric applications, aimed at better monitoring
users’ activities, understanding their habits and detecting
their identity. Following this trend, this paper investigates whether
the electrical energy consumption of a user can be a distinctive
behavioural biometric trait. In particular we analyse daily and
weekly load profiles showing that they are closely related to
the identity of the users. Hence, we believe that this level of
analysis can open interesting application scenarios in the field of
energy management and it provides a good working framework
for the continuous development of smart environments with
demonstrable benefits on real-world implementations.
124.
Alan, Alper; Costanza, Enrico; Fischer, J.; Ramchurn, Sarvapali; Rodden, T.; Jennings, N. R.
A field study of human-agent interaction for electricity tariff switching Proceedings Article
In: Proceedings of the 13th International Conference on Autonomous Agents and Multi-Agent Systems, 2014.
@inproceedings{eps360820,
title = {A field study of human-agent interaction for electricity tariff switching},
author = {Alper Alan and Enrico Costanza and J. Fischer and Sarvapali Ramchurn and T. Rodden and N. R. Jennings},
url = {http://eprints.soton.ac.uk/360820/},
year = {2014},
date = {2014-01-01},
booktitle = {Proceedings of the 13th International Conference on Autonomous Agents and Multi-Agent Systems},
abstract = {Recently, many algorithms have been developed for autonomous agents to manage home energy use on behalf of their human owners. By so doing, it is expected that agents will be more efficient at, for example, choosing the best energy tariff to switch to when dynamically priced tariffs come about. However, to date, there has been no validation of such technologies in any field trial. In particular, it has not been shown whether users prefer fully autonomous agents as opposed to controlling their preferences manually. Hence, in this paper we describe a novel platform, called Tariff Agent, to study notions of flexible autonomy in the context of tariff switching. Tariff Agent uses real-world datasets and real-time electricity monitoring to instantiate a scenario where human participants may have to make, or delegate to their agent (in different ways), tariff switching decisions given uncertainties about their own consumption and tariff prices. We carried out a field trial with 10 participants and, from both quantitative and qualitative results, formulate novel design guidelines for systems that implement flexible autonom.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Recently, many algorithms have been developed for autonomous agents to manage home energy use on behalf of their human owners. By so doing, it is expected that agents will be more efficient at, for example, choosing the best energy tariff to switch to when dynamically priced tariffs come about. However, to date, there has been no validation of such technologies in any field trial. In particular, it has not been shown whether users prefer fully autonomous agents as opposed to controlling their preferences manually. Hence, in this paper we describe a novel platform, called Tariff Agent, to study notions of flexible autonomy in the context of tariff switching. Tariff Agent uses real-world datasets and real-time electricity monitoring to instantiate a scenario where human participants may have to make, or delegate to their agent (in different ways), tariff switching decisions given uncertainties about their own consumption and tariff prices. We carried out a field trial with 10 participants and, from both quantitative and qualitative results, formulate novel design guidelines for systems that implement flexible autonom.
125.
Costanza, Enrico; Fischer, Joel E; Colley, James A; Rodden, Tom; Ramchurn, Sarvapali; Jennings, Nicholas R.
Doing the laundry with agents: a field trial of a future smart energy system in the home Proceedings Article
In: ACM CHI Conference on Human Factors in Computing Systems 2014, pp. 813–822, ACM 2014.
@inproceedings{eps361173,
title = {Doing the laundry with agents: a field trial of a future smart energy system in the home},
author = {Enrico Costanza and Joel E Fischer and James A Colley and Tom Rodden and Sarvapali Ramchurn and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/361173/},
year = {2014},
date = {2014-01-01},
booktitle = {ACM CHI Conference on Human Factors in Computing Systems 2014},
pages = {813–822},
organization = {ACM},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
126.
Tran-Thanh, Long; Huynh, Trung Dong; Rosenfield, A; Ramchurn, Sarvapali; Jennings, Nicholas R.
BudgetFix: budget limited crowdsourcing for interdependent task allocation with quality guarantees Proceedings Article
In: 13th International Conference on Autonomous Agents and Multi-Agent Systems, International Foundation for Autonomous Agents and Multiagent Systems, 2014.
@inproceedings{eps362321,
title = {BudgetFix: budget limited crowdsourcing for interdependent task allocation with quality guarantees},
author = {Long Tran-Thanh and Trung Dong Huynh and A Rosenfield and Sarvapali Ramchurn and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/362321/},
year = {2014},
date = {2014-01-01},
booktitle = {13th International Conference on Autonomous Agents and Multi-Agent Systems},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
127.
Vinyals, Meritxell; Macarthur, Kathryn; Farinelli, Alessandro; Ramchurn, Sarvapali; Jennings, Nicholas R.
A message-passing approach to decentralised parallel machine scheduling Journal Article
In: The Computer Journal, 2014.
@article{eps360818,
title = {A message-passing approach to decentralised parallel machine scheduling},
author = {Meritxell Vinyals and Kathryn Macarthur and Alessandro Farinelli and Sarvapali Ramchurn and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/360818/},
year = {2014},
date = {2014-01-01},
journal = {The Computer Journal},
publisher = {Oxford University Press},
abstract = {This paper tackles the problem of parallelizing heterogeneous computational tasks across a number of computational nodes (aka agents) where each agent may not be able to perform all the tasks and may have different computational speeds. An equivalent problem can be found in operations research, and it is known as scheduling tasks on unrelated parallel machines (also known as R?Cmax). Given this equivalence observation, we present the spanning tree decentralized task distribution algorithm (ST-DTDA), the first decentralized solution to R?Cmax. ST-DTDA achieves decomposition by means of the min?max algorithm, a member of the generalized distributive law family, that performs inference by message-passing along the edges of a graphical model (known as a junction tree). Specifically, ST-DTDA uses min?max to optimally solve an approximation of the original R?Cmax problem that results from eliminating possible agent-task allocations until it is mapped into an acyclic structure. To eliminate those allocations that are least likely to have an impact on the solution quality, ST-DTDA uses a heuristic approach. Moreover, ST-DTDA provides a per-instance approximation ratio that guarantees that the makespan of its solution (optimal in the approximated R?Cmax problem) is not more than a factor ensuremathrho times the makespan of the optimal of the original problem. In our empirical evaluation of ST-DTDA, we show that ST-DTDA, with a min-regret heuristic, converges to solutions that are between 78 and 95% optimal whilst providing approximation ratios lower than 3.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper tackles the problem of parallelizing heterogeneous computational tasks across a number of computational nodes (aka agents) where each agent may not be able to perform all the tasks and may have different computational speeds. An equivalent problem can be found in operations research, and it is known as scheduling tasks on unrelated parallel machines (also known as R?Cmax). Given this equivalence observation, we present the spanning tree decentralized task distribution algorithm (ST-DTDA), the first decentralized solution to R?Cmax. ST-DTDA achieves decomposition by means of the min?max algorithm, a member of the generalized distributive law family, that performs inference by message-passing along the edges of a graphical model (known as a junction tree). Specifically, ST-DTDA uses min?max to optimally solve an approximation of the original R?Cmax problem that results from eliminating possible agent-task allocations until it is mapped into an acyclic structure. To eliminate those allocations that are least likely to have an impact on the solution quality, ST-DTDA uses a heuristic approach. Moreover, ST-DTDA provides a per-instance approximation ratio that guarantees that the makespan of its solution (optimal in the approximated R?Cmax problem) is not more than a factor ensuremathrho times the makespan of the optimal of the original problem. In our empirical evaluation of ST-DTDA, we show that ST-DTDA, with a min-regret heuristic, converges to solutions that are between 78 and 95% optimal whilst providing approximation ratios lower than 3.
128.
Fischer, J. E.; Jiang, W; Kerne, A; Greenhalgh, C; Ramchurn, Sarvapali D; Reece, Steven; Pantidi, N; Rodden, T
Supporting Team Coordination on the Ground: Requirements from a Mixed Reality Game. Proceedings Article
In: 11th Int. Conference on the Design of Cooperative Systems (COOP ?14), 2014.
@inproceedings{orchid192,
title = {Supporting Team Coordination on the Ground: Requirements from a Mixed Reality Game.},
author = {J. E. Fischer and W Jiang and A Kerne and C Greenhalgh and Sarvapali D Ramchurn and Steven Reece and N Pantidi and T Rodden},
year = {2014},
date = {2014-01-01},
booktitle = {11th Int. Conference on the Design of Cooperative Systems (COOP ?14)},
howpublished = {http://www.orchid.ac.uk/eprints/192/1/COOP2014-Fischer-author-version.pdf},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
129.
Jiang, W; Fischer, J. E.; Greenhalgh, C; Ramchurn, Sarvapali D; Wu, Feng; Jennings, Nicholas R; Rodden, T
Social Implications of Agent-based Planning Support for Human Teams. Proceedings Article
In: 2014 Int. Conference on Collaboration Technologies and Systems, 2014.
@inproceedings{orchid191,
title = {Social Implications of Agent-based Planning Support for Human Teams.},
author = {W Jiang and J. E. Fischer and C Greenhalgh and Sarvapali D Ramchurn and Feng Wu and Nicholas R Jennings and T Rodden},
year = {2014},
date = {2014-01-01},
booktitle = {2014 Int. Conference on Collaboration Technologies and Systems},
howpublished = {http://www.orchid.ac.uk/eprints/191/1/CTS2014-Jiang-author-version.pdf},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
130.
Pawlowski, Krzysztof; Kurach, Karol; Svensson, Kim; Ramchurn, Sarvapali D; Michalak, Tomasz; Rahwan, Talal
Coalition Structure Generation with the Graphics Processing Unit Proceedings Article
In: 13th Int. Conf. on Autonomous Agents and Multi-Agent Systems, 2014.
@inproceedings{orchid176,
title = {Coalition Structure Generation with the Graphics Processing Unit},
author = {Krzysztof Pawlowski and Karol Kurach and Kim Svensson and Sarvapali D Ramchurn and Tomasz Michalak and Talal Rahwan},
year = {2014},
date = {2014-01-01},
booktitle = {13th Int. Conf. on Autonomous Agents and Multi-Agent Systems},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
131.
Huynh, Trung Dong; Ebden, Mark; Ramchurn, Sarvapali; Roberts, Stephen; Moreau, Luc
Data quality assessment from provenance graphs Proceedings Article
In: Provenance Analytics 2014, 2014.
@inproceedings{eps365510,
title = {Data quality assessment from provenance graphs},
author = {Trung Dong Huynh and Mark Ebden and Sarvapali Ramchurn and Stephen Roberts and Luc Moreau},
url = {http://eprints.soton.ac.uk/365510/},
year = {2014},
date = {2014-01-01},
booktitle = {Provenance Analytics 2014},
abstract = {Provenance is a domain-independent means to represent what happened in an application, which can help verify data and infer data quality. Provenance patterns can manifest real-world phenomena such as a significant interest in a piece of content, providing an indication of its quality, or even issues such as undesirable interactions within a group of contributors. This paper presents an application-independent methodology for analyzing data based on the network metrics of provenance graphs to learn about such patterns and to relate them to data quality in an automated manner. Validating this method on the provenance records of CollabMap, an online crowdsourcing mapping application, we demonstrated an accuracy level of over 95% for the trust classification of data generated by the crowd therein.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Provenance is a domain-independent means to represent what happened in an application, which can help verify data and infer data quality. Provenance patterns can manifest real-world phenomena such as a significant interest in a piece of content, providing an indication of its quality, or even issues such as undesirable interactions within a group of contributors. This paper presents an application-independent methodology for analyzing data based on the network metrics of provenance graphs to learn about such patterns and to relate them to data quality in an automated manner. Validating this method on the provenance records of CollabMap, an online crowdsourcing mapping application, we demonstrated an accuracy level of over 95% for the trust classification of data generated by the crowd therein.
132.
Jennings, Nicholas R.; Moreau, Luc; Nicholson, D; Ramchurn, Sarvapali D.; Roberts, S; Rodden, T; Rogers, Alex
On human-agent collectives Journal Article
In: Communications of the ACM, vol. 57, no. 12, pp. 33-42, 2014.
@article{eps364593,
title = {On human-agent collectives},
author = {Nicholas R. Jennings and Luc Moreau and D Nicholson and Sarvapali D. Ramchurn and S Roberts and T Rodden and Alex Rogers},
url = {http://eprints.soton.ac.uk/364593/},
year = {2014},
date = {2014-01-01},
journal = {Communications of the ACM},
volume = {57},
number = {12},
pages = {33-42},
abstract = {We live in a world where a host of computer systems, distributed throughout our physical and information environments, are increasingly implicated in our everyday actions. Computer technologies impact all aspects of our lives and our relationship with the digital has fundamentally altered as computers have moved out of the workplace and away from the desktop. Networked computers, tablets, phones and personal devices are now commonplace, as are an increasingly diverse set of digital devices built into the world around us. Data and information is generated at unprecedented speeds and volumes from an increasingly diverse range of sources. It is then combined in unforeseen ways, limited only by human imagination. People?s activities and collaborations are becoming ever more dependent upon and intertwined with this ubiquitous information substrate. As these trends continue apace, it is becoming apparent that many endeavours involve the symbiotic interleaving of humans and computers. Moreover, the emergence of these close-knit partnerships is inducing profound change. Rather than issuing instructions to passive machines that wait until they are asked before doing anything, we will work in tandem with highly inter-connected computational components that act autonomously and intelligently (aka agents). As a consequence, greater attention needs to be given to the balance of control between people and machines. In many situations, humans will be in charge and agents will predominantly act in a supporting role. In other cases, however, the agents will be in control and humans will play the supporting role. We term this emerging class of systems human-agent collectives (HACs) to reflect the close partnership and the flexible social interactions between the humans and the computers. As well as exhibiting increased autonomy, such systems will be inherently open and social. This means the participants will need to continually and flexibly establish and manage a range of social relationships. Thus, depending on the task at hand, different constellations of people, resources, and information will need to come together, operate in a coordinated fashion, and then disband. The openness and presence of many distinct stakeholders means participation will be motivated by a broad range of incentives rather than diktat. This article outlines the key research challenges involved in developing a comprehensive understanding of HACs. To illuminate this agenda, a nascent application in the domain of disaster response is presented.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We live in a world where a host of computer systems, distributed throughout our physical and information environments, are increasingly implicated in our everyday actions. Computer technologies impact all aspects of our lives and our relationship with the digital has fundamentally altered as computers have moved out of the workplace and away from the desktop. Networked computers, tablets, phones and personal devices are now commonplace, as are an increasingly diverse set of digital devices built into the world around us. Data and information is generated at unprecedented speeds and volumes from an increasingly diverse range of sources. It is then combined in unforeseen ways, limited only by human imagination. People?s activities and collaborations are becoming ever more dependent upon and intertwined with this ubiquitous information substrate. As these trends continue apace, it is becoming apparent that many endeavours involve the symbiotic interleaving of humans and computers. Moreover, the emergence of these close-knit partnerships is inducing profound change. Rather than issuing instructions to passive machines that wait until they are asked before doing anything, we will work in tandem with highly inter-connected computational components that act autonomously and intelligently (aka agents). As a consequence, greater attention needs to be given to the balance of control between people and machines. In many situations, humans will be in charge and agents will predominantly act in a supporting role. In other cases, however, the agents will be in control and humans will play the supporting role. We term this emerging class of systems human-agent collectives (HACs) to reflect the close partnership and the flexible social interactions between the humans and the computers. As well as exhibiting increased autonomy, such systems will be inherently open and social. This means the participants will need to continually and flexibly establish and manage a range of social relationships. Thus, depending on the task at hand, different constellations of people, resources, and information will need to come together, operate in a coordinated fashion, and then disband. The openness and presence of many distinct stakeholders means participation will be motivated by a broad range of incentives rather than diktat. This article outlines the key research challenges involved in developing a comprehensive understanding of HACs. To illuminate this agenda, a nascent application in the domain of disaster response is presented.
133.
Bistaffa, Filippo; Farinelli, Alessandro; Cerquides, Jesus; Rodriguez-Aguilar, Juan Antonio; Ramchurn, Sarvapali D
Anytime Coalition Structure Generation on Synergy Graphs Proceedings Article
In: 13th Int. Conf. on Autonomous Agents and Multi-Agent Systems, pp. 13-20, 2014.
@inproceedings{orchid175,
title = {Anytime Coalition Structure Generation on Synergy Graphs},
author = {Filippo Bistaffa and Alessandro Farinelli and Jesus Cerquides and Juan Antonio Rodriguez-Aguilar and Sarvapali D Ramchurn},
url = {http://aamas2014.lip6.fr/proceedings/aamas/p13.pdf},
year = {2014},
date = {2014-01-01},
booktitle = {13th Int. Conf. on Autonomous Agents and Multi-Agent Systems},
pages = {13-20},
abstract = {We consider the coalition structure generation (CSG) problem on
synergy graphs, which arises in many practical applications where
communication constraints, social or trust relationships must be
taken into account when forming coalitions. We propose a novel
representation of this problem based on the concept of edge contraction,
and an innovative branch and bound approach (CFSS),
which is particularly efficient when applied to a general class of
characteristic functions. This new model provides a non-redundant
partition of the search space, hence allowing an effective parallelisation.
We evaluate CFSS on two benchmark functions, the edge
sum with coordination cost and the collective energy purchasing
functions, comparing its performance with the best algorithm for
CSG on synergy graphs: DyCE. The latter approach is centralised
and cannot be efficiently parallelised due to the exponential memory
requirements in the number of agents, which limits its scalability
(while CFSS memory requirements are only polynomial).
Our results show that, when the graphs are very sparse, CFSS is
4 orders of magnitude faster than DyCE. Moreover, CFSS is the
first approach to provide anytime approximate solutions with quality
guarantees for very large systems (i.e., with more than 2700
agents).},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We consider the coalition structure generation (CSG) problem on
synergy graphs, which arises in many practical applications where
communication constraints, social or trust relationships must be
taken into account when forming coalitions. We propose a novel
representation of this problem based on the concept of edge contraction,
and an innovative branch and bound approach (CFSS),
which is particularly efficient when applied to a general class of
characteristic functions. This new model provides a non-redundant
partition of the search space, hence allowing an effective parallelisation.
We evaluate CFSS on two benchmark functions, the edge
sum with coordination cost and the collective energy purchasing
functions, comparing its performance with the best algorithm for
CSG on synergy graphs: DyCE. The latter approach is centralised
and cannot be efficiently parallelised due to the exponential memory
requirements in the number of agents, which limits its scalability
(while CFSS memory requirements are only polynomial).
Our results show that, when the graphs are very sparse, CFSS is
4 orders of magnitude faster than DyCE. Moreover, CFSS is the
first approach to provide anytime approximate solutions with quality
guarantees for very large systems (i.e., with more than 2700
agents).
synergy graphs, which arises in many practical applications where
communication constraints, social or trust relationships must be
taken into account when forming coalitions. We propose a novel
representation of this problem based on the concept of edge contraction,
and an innovative branch and bound approach (CFSS),
which is particularly efficient when applied to a general class of
characteristic functions. This new model provides a non-redundant
partition of the search space, hence allowing an effective parallelisation.
We evaluate CFSS on two benchmark functions, the edge
sum with coordination cost and the collective energy purchasing
functions, comparing its performance with the best algorithm for
CSG on synergy graphs: DyCE. The latter approach is centralised
and cannot be efficiently parallelised due to the exponential memory
requirements in the number of agents, which limits its scalability
(while CFSS memory requirements are only polynomial).
Our results show that, when the graphs are very sparse, CFSS is
4 orders of magnitude faster than DyCE. Moreover, CFSS is the
first approach to provide anytime approximate solutions with quality
guarantees for very large systems (i.e., with more than 2700
agents).
134.
Alam, Muddasser; Alan, Alper; Rogers, Alex; Ramchurn, Sarvapali D.
Towards a smart home framework Proceedings Article
In: 5th ACM Workshop On Embedded Systems For Energy-Efficient Buildings (BuildSys2013), 2013.
@inproceedings{eps357187,
title = {Towards a smart home framework},
author = {Muddasser Alam and Alper Alan and Alex Rogers and Sarvapali D. Ramchurn},
url = {http://eprints.soton.ac.uk/357187/},
year = {2013},
date = {2013-01-01},
booktitle = {5th ACM Workshop On Embedded Systems For Energy-Efficient Buildings (BuildSys2013)},
abstract = {We present our Smart Home Framework (SHF) which simplifies the modelling, prototyping and simulation of smart infrastructure (i.e., smart home and smart communities). It provides the buildings blocks (e.g., home appliances) that can be extended and assembled together to build a smart infrastructure model to which appropriate AI techniques can be applied. This approach enables rapid modelling where new research initiatives can build on existing work.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We present our Smart Home Framework (SHF) which simplifies the modelling, prototyping and simulation of smart infrastructure (i.e., smart home and smart communities). It provides the buildings blocks (e.g., home appliances) that can be extended and assembled together to build a smart infrastructure model to which appropriate AI techniques can be applied. This approach enables rapid modelling where new research initiatives can build on existing work.
135.
Alam, Muddasser; Ramchurn, Sarvapali; Rogers, Alex
Cooperative energy exchange for the efficient use of energy and resources in remote communities. [Winner, Best Student Paper Award at AAMAS2013] Proceedings Article
In: Twelfth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2013), 2013.
@inproceedings{eps346637,
title = {Cooperative energy exchange for the efficient use of energy and resources in remote communities. [Winner, Best Student Paper Award at AAMAS2013]},
author = {Muddasser Alam and Sarvapali Ramchurn and Alex Rogers},
url = {http://eprints.soton.ac.uk/346637/},
year = {2013},
date = {2013-01-01},
booktitle = {Twelfth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2013)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
136.
Alam, Muddasser; Rogers, Alex; Ramchurn, Sarvapali
Interdependent multi-issue negotiation for energy exchange in remote communities Proceedings Article
In: Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13), 2013.
@inproceedings{eps350941,
title = {Interdependent multi-issue negotiation for energy exchange in remote communities},
author = {Muddasser Alam and Alex Rogers and Sarvapali Ramchurn},
url = {http://eprints.soton.ac.uk/350941/},
year = {2013},
date = {2013-01-01},
booktitle = {Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13)},
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 protocol imposes restrictions over negotiation such that it reduces the complex interdependent multi-issue negotiation to one where agents have a strategy profile in subgame perfect Nash equilibrium. We show that our negotiation protocol is tractable, concurrent, scalable and leads to Pareto-optimal outcomes in a decentralised manner. We empirically evaluate our protocol and show that, in this instance, a society of agents can (i) improve the overall utilities by 14% and (ii) reduce their overall use of the batteries by 37%},
keywords = {},
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 protocol imposes restrictions over negotiation such that it reduces the complex interdependent multi-issue negotiation to one where agents have a strategy profile in subgame perfect Nash equilibrium. We show that our negotiation protocol is tractable, concurrent, scalable and leads to Pareto-optimal outcomes in a decentralised manner. We empirically evaluate our protocol and show that, in this instance, a society of agents can (i) improve the overall utilities by 14% and (ii) reduce their overall use of the batteries by 37%
137.
Alam, Muddasser; Rogers, Alex; Ramchurn, Sarvapali D.
Interdependent multi-issue negotiation for energy exchange in remote communities Proceedings Article
In: International Workshop on AI Problems and Approaches for Intelligent Environments (AI4IE), 2013.
@inproceedings{eps357186,
title = {Interdependent multi-issue negotiation for energy exchange in remote communities},
author = {Muddasser Alam and Alex Rogers and Sarvapali D. Ramchurn},
url = {http://eprints.soton.ac.uk/357186/},
year = {2013},
date = {2013-01-01},
booktitle = {International Workshop on AI Problems and Approaches for Intelligent Environments (AI4IE)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
138.
Cerquides, Jesus; Farinelli, Alessandro; Meseguer, Pedro; Ramchurn, Sarvapali
A tutorial on optimisation for multi-agent systems Journal Article
In: The Computer Journal, pp. 1–26, 2013.
@article{eps361998,
title = {A tutorial on optimisation for multi-agent systems},
author = {Jesus Cerquides and Alessandro Farinelli and Pedro Meseguer and Sarvapali Ramchurn},
url = {http://eprints.soton.ac.uk/361998/},
year = {2013},
date = {2013-01-01},
journal = {The Computer Journal},
pages = {1–26},
abstract = {Research on optimization in multi-agent systems (MASs) has contributed with a wealth of techniques to solve many of the challenges arising in a wide range of multi-agent application domains. Multi-agent optimization focuses on casting MAS problems into optimization problems. The solving of those problems could possibly involve the active participation of the agents in a MAS. Research on multi-agent optimization has rapidly become a very technical, specialized field. Moreover, the contributions to the field in the literature are largely scattered. These two factors dramatically hinder access to a basic, general view of the foundations of the field. This tutorial is intended to ease such access by providing a gentle introduction to fundamental concepts and techniques on multi-agent optimization},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Research on optimization in multi-agent systems (MASs) has contributed with a wealth of techniques to solve many of the challenges arising in a wide range of multi-agent application domains. Multi-agent optimization focuses on casting MAS problems into optimization problems. The solving of those problems could possibly involve the active participation of the agents in a MAS. Research on multi-agent optimization has rapidly become a very technical, specialized field. Moreover, the contributions to the field in the literature are largely scattered. These two factors dramatically hinder access to a basic, general view of the foundations of the field. This tutorial is intended to ease such access by providing a gentle introduction to fundamental concepts and techniques on multi-agent optimization
139.
Farinelli, Alessandro; Bicego, Manuele; Ramchurn, Sarvapali; Zuchelli, Marco
C-Link: a hierarchical clustering approach to large-scale near-optimal coalition formation Proceedings Article
In: 23rd International Joint Conference on Artificial Intelligence, AAAI Press / International Joint Conferences on Artificial Intelligence, 2013.
@inproceedings{eps351521,
title = {C-Link: a hierarchical clustering approach to large-scale near-optimal coalition formation},
author = {Alessandro Farinelli and Manuele Bicego and Sarvapali Ramchurn and Marco Zuchelli},
url = {http://eprints.soton.ac.uk/351521/},
year = {2013},
date = {2013-01-01},
booktitle = {23rd International Joint Conference on Artificial Intelligence},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
abstract = {Coalition formation is a fundamental approach to multi-agent coordination. In this paper we address the specific problem of coalition structure generation, and focus on providing good-enough solutions using a novel heuristic approach that is based on data clustering methods. In particular, we propose a hierarchical agglomerative clustering approach (C-Link), which uses a similarity criterion between coalitions based on the gain that the system achieves if two coalitions merge. We empirically evaluate C-Link on a synthetic benchmark data-set as well as in collective energy purchasing settings. Our results show that the C-link approach performs very well against an optimal benchmark based on Mixed-Integer Programming, achieving solutions which are in the worst case about 80% of the optimal (in the synthetic data-set), and 98% of the optimal (in the energy data-set). Thus we show that C-Link can return solutions for problems involving thousands of agents within minutes.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Coalition formation is a fundamental approach to multi-agent coordination. In this paper we address the specific problem of coalition structure generation, and focus on providing good-enough solutions using a novel heuristic approach that is based on data clustering methods. In particular, we propose a hierarchical agglomerative clustering approach (C-Link), which uses a similarity criterion between coalitions based on the gain that the system achieves if two coalitions merge. We empirically evaluate C-Link on a synthetic benchmark data-set as well as in collective energy purchasing settings. Our results show that the C-link approach performs very well against an optimal benchmark based on Mixed-Integer Programming, achieving solutions which are in the worst case about 80% of the optimal (in the synthetic data-set), and 98% of the optimal (in the energy data-set). Thus we show that C-Link can return solutions for problems involving thousands of agents within minutes.
140.
Fischer, Joel E.; Ramchurn, Sarvapali D.; Osborne, Michael A.; Parson, Oliver; Huynh, Trung Dong; Alam, Muddasser; Pantidi, Nadia; Moran, Stuart; Bachour, Khaled; Reece, Steven; Costanza, Enrico; Rodden, Tom; Jennings, Nicholas R.
Recommending Energy Tariffs and Load Shifting Based on Smart Household Usage Profiling Proceedings Article
In: International Conference on Intelligent User Interfaces, pp. 383–394, 2013.
@inproceedings{eps346991,
title = {Recommending Energy Tariffs and Load Shifting Based on Smart Household Usage Profiling},
author = {Joel E. Fischer and Sarvapali D. Ramchurn and Michael A. Osborne and Oliver Parson and Trung Dong Huynh and Muddasser Alam and Nadia Pantidi and Stuart Moran and Khaled Bachour and Steven Reece and Enrico Costanza and Tom Rodden and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/346991/},
year = {2013},
date = {2013-01-01},
booktitle = {International Conference on Intelligent User Interfaces},
pages = {383–394},
abstract = {We present a system and study of personalized energy-related recommendation. AgentSwitch utilizes electricity usage data collected from users' households over a period of time to realize a range of smart energy-related recommendations on energy tariffs, load detection and usage shifting. The web service is driven by a third party real-time energy tariff API (uSwitch), an energy data store, a set of algorithms for usage prediction, and appliance-level load disaggregation. We present the system design and user evaluation consisting of interviews and interface walkthroughs. We recruited participants from a previous study during which three months of their household's energy use was recorded to evaluate personalized recommendations in AgentSwitch. Our contributions are a) a systems architecture for personalized energy services; and b) findings from the evaluation that reveal challenges in designing energy-related recommender systems. In response to the challenges we formulate design recommendations to mitigate barriers to switching tariffs, to incentivize load shifting, and to automate energy management.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We present a system and study of personalized energy-related recommendation. AgentSwitch utilizes electricity usage data collected from users' households over a period of time to realize a range of smart energy-related recommendations on energy tariffs, load detection and usage shifting. The web service is driven by a third party real-time energy tariff API (uSwitch), an energy data store, a set of algorithms for usage prediction, and appliance-level load disaggregation. We present the system design and user evaluation consisting of interviews and interface walkthroughs. We recruited participants from a previous study during which three months of their household's energy use was recorded to evaluate personalized recommendations in AgentSwitch. Our contributions are a) a systems architecture for personalized energy services; and b) findings from the evaluation that reveal challenges in designing energy-related recommender systems. In response to the challenges we formulate design recommendations to mitigate barriers to switching tariffs, to incentivize load shifting, and to automate energy management.
Sorry, no publications matched your criteria.
121.
Chen, S.; Wu, F.; Shen, L.; Chen, J.; Ramchurn, S. D.
Decentralized Patrolling Under Constraints in Dynamic Environments Journal Article
In: Cybernetics, IEEE Transactions on, vol. PP, no. 99, pp. 1-13, 2015, ISSN: 2168-2267.
@article{7362160,
title = {Decentralized Patrolling Under Constraints in Dynamic Environments},
author = {S. Chen and F. Wu and L. Shen and J. Chen and S. D. Ramchurn},
doi = {10.1109/TCYB.2015.2505737},
issn = {2168-2267},
year = {2015},
date = {2015-01-01},
journal = {Cybernetics, IEEE Transactions on},
volume = {PP},
number = {99},
pages = {1-13},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
122.
Kalyanaraman, Shivkumar; Seetharam, Deva P; Shorey, Rajeev; Ramchurn, Sarvapali D; Srivastava, Mani (Ed.)
ACM, 2015, ISBN: 978-1-4503-3609-3.
@proceedings{DBLP:conf/eenergy/2015,
title = {Proceedings of the 2015 ACM Sixth International Conference on Future
Energy Systems, e-Energy 2015, Bangalore, India, July 14-17, 2015},
editor = {Shivkumar Kalyanaraman and Deva P Seetharam and Rajeev Shorey and Sarvapali D Ramchurn and Mani Srivastava},
url = {http://dl.acm.org/citation.cfm?id=2768510},
isbn = {978-1-4503-3609-3},
year = {2015},
date = {2015-01-01},
publisher = {ACM},
keywords = {},
pubstate = {published},
tppubtype = {proceedings}
}
123.
Bicego, A. Farinelli F. Recchia M.
Behavioural biometrics using electricity load profiles Journal Article
In: Proceedings of the International Conference on Pattern Recognition, 2014.
@article{bicego:etal:2014,
title = {Behavioural biometrics using electricity load profiles},
author = {A. Farinelli F. Recchia M. Bicego},
url = {https://www.sramchurn.com/wp-content/uploads/2014/10/CR_v1.pdf},
year = {2014},
date = {2014-08-24},
journal = {Proceedings of the International Conference on Pattern Recognition},
abstract = {Modelling behavioural biometric patterns is a key
issue for modern user centric applications, aimed at better monitoring
users’ activities, understanding their habits and detecting
their identity. Following this trend, this paper investigates whether
the electrical energy consumption of a user can be a distinctive
behavioural biometric trait. In particular we analyse daily and
weekly load profiles showing that they are closely related to
the identity of the users. Hence, we believe that this level of
analysis can open interesting application scenarios in the field of
energy management and it provides a good working framework
for the continuous development of smart environments with
demonstrable benefits on real-world implementations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Modelling behavioural biometric patterns is a key
issue for modern user centric applications, aimed at better monitoring
users’ activities, understanding their habits and detecting
their identity. Following this trend, this paper investigates whether
the electrical energy consumption of a user can be a distinctive
behavioural biometric trait. In particular we analyse daily and
weekly load profiles showing that they are closely related to
the identity of the users. Hence, we believe that this level of
analysis can open interesting application scenarios in the field of
energy management and it provides a good working framework
for the continuous development of smart environments with
demonstrable benefits on real-world implementations.
issue for modern user centric applications, aimed at better monitoring
users’ activities, understanding their habits and detecting
their identity. Following this trend, this paper investigates whether
the electrical energy consumption of a user can be a distinctive
behavioural biometric trait. In particular we analyse daily and
weekly load profiles showing that they are closely related to
the identity of the users. Hence, we believe that this level of
analysis can open interesting application scenarios in the field of
energy management and it provides a good working framework
for the continuous development of smart environments with
demonstrable benefits on real-world implementations.
124.
Alan, Alper; Costanza, Enrico; Fischer, J.; Ramchurn, Sarvapali; Rodden, T.; Jennings, N. R.
A field study of human-agent interaction for electricity tariff switching Proceedings Article
In: Proceedings of the 13th International Conference on Autonomous Agents and Multi-Agent Systems, 2014.
@inproceedings{eps360820,
title = {A field study of human-agent interaction for electricity tariff switching},
author = {Alper Alan and Enrico Costanza and J. Fischer and Sarvapali Ramchurn and T. Rodden and N. R. Jennings},
url = {http://eprints.soton.ac.uk/360820/},
year = {2014},
date = {2014-01-01},
booktitle = {Proceedings of the 13th International Conference on Autonomous Agents and Multi-Agent Systems},
abstract = {Recently, many algorithms have been developed for autonomous agents to manage home energy use on behalf of their human owners. By so doing, it is expected that agents will be more efficient at, for example, choosing the best energy tariff to switch to when dynamically priced tariffs come about. However, to date, there has been no validation of such technologies in any field trial. In particular, it has not been shown whether users prefer fully autonomous agents as opposed to controlling their preferences manually. Hence, in this paper we describe a novel platform, called Tariff Agent, to study notions of flexible autonomy in the context of tariff switching. Tariff Agent uses real-world datasets and real-time electricity monitoring to instantiate a scenario where human participants may have to make, or delegate to their agent (in different ways), tariff switching decisions given uncertainties about their own consumption and tariff prices. We carried out a field trial with 10 participants and, from both quantitative and qualitative results, formulate novel design guidelines for systems that implement flexible autonom.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Recently, many algorithms have been developed for autonomous agents to manage home energy use on behalf of their human owners. By so doing, it is expected that agents will be more efficient at, for example, choosing the best energy tariff to switch to when dynamically priced tariffs come about. However, to date, there has been no validation of such technologies in any field trial. In particular, it has not been shown whether users prefer fully autonomous agents as opposed to controlling their preferences manually. Hence, in this paper we describe a novel platform, called Tariff Agent, to study notions of flexible autonomy in the context of tariff switching. Tariff Agent uses real-world datasets and real-time electricity monitoring to instantiate a scenario where human participants may have to make, or delegate to their agent (in different ways), tariff switching decisions given uncertainties about their own consumption and tariff prices. We carried out a field trial with 10 participants and, from both quantitative and qualitative results, formulate novel design guidelines for systems that implement flexible autonom.
125.
Costanza, Enrico; Fischer, Joel E; Colley, James A; Rodden, Tom; Ramchurn, Sarvapali; Jennings, Nicholas R.
Doing the laundry with agents: a field trial of a future smart energy system in the home Proceedings Article
In: ACM CHI Conference on Human Factors in Computing Systems 2014, pp. 813–822, ACM 2014.
@inproceedings{eps361173,
title = {Doing the laundry with agents: a field trial of a future smart energy system in the home},
author = {Enrico Costanza and Joel E Fischer and James A Colley and Tom Rodden and Sarvapali Ramchurn and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/361173/},
year = {2014},
date = {2014-01-01},
booktitle = {ACM CHI Conference on Human Factors in Computing Systems 2014},
pages = {813–822},
organization = {ACM},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
126.
Tran-Thanh, Long; Huynh, Trung Dong; Rosenfield, A; Ramchurn, Sarvapali; Jennings, Nicholas R.
BudgetFix: budget limited crowdsourcing for interdependent task allocation with quality guarantees Proceedings Article
In: 13th International Conference on Autonomous Agents and Multi-Agent Systems, International Foundation for Autonomous Agents and Multiagent Systems, 2014.
@inproceedings{eps362321,
title = {BudgetFix: budget limited crowdsourcing for interdependent task allocation with quality guarantees},
author = {Long Tran-Thanh and Trung Dong Huynh and A Rosenfield and Sarvapali Ramchurn and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/362321/},
year = {2014},
date = {2014-01-01},
booktitle = {13th International Conference on Autonomous Agents and Multi-Agent Systems},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
127.
Vinyals, Meritxell; Macarthur, Kathryn; Farinelli, Alessandro; Ramchurn, Sarvapali; Jennings, Nicholas R.
A message-passing approach to decentralised parallel machine scheduling Journal Article
In: The Computer Journal, 2014.
@article{eps360818,
title = {A message-passing approach to decentralised parallel machine scheduling},
author = {Meritxell Vinyals and Kathryn Macarthur and Alessandro Farinelli and Sarvapali Ramchurn and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/360818/},
year = {2014},
date = {2014-01-01},
journal = {The Computer Journal},
publisher = {Oxford University Press},
abstract = {This paper tackles the problem of parallelizing heterogeneous computational tasks across a number of computational nodes (aka agents) where each agent may not be able to perform all the tasks and may have different computational speeds. An equivalent problem can be found in operations research, and it is known as scheduling tasks on unrelated parallel machines (also known as R?Cmax). Given this equivalence observation, we present the spanning tree decentralized task distribution algorithm (ST-DTDA), the first decentralized solution to R?Cmax. ST-DTDA achieves decomposition by means of the min?max algorithm, a member of the generalized distributive law family, that performs inference by message-passing along the edges of a graphical model (known as a junction tree). Specifically, ST-DTDA uses min?max to optimally solve an approximation of the original R?Cmax problem that results from eliminating possible agent-task allocations until it is mapped into an acyclic structure. To eliminate those allocations that are least likely to have an impact on the solution quality, ST-DTDA uses a heuristic approach. Moreover, ST-DTDA provides a per-instance approximation ratio that guarantees that the makespan of its solution (optimal in the approximated R?Cmax problem) is not more than a factor ensuremathrho times the makespan of the optimal of the original problem. In our empirical evaluation of ST-DTDA, we show that ST-DTDA, with a min-regret heuristic, converges to solutions that are between 78 and 95% optimal whilst providing approximation ratios lower than 3.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper tackles the problem of parallelizing heterogeneous computational tasks across a number of computational nodes (aka agents) where each agent may not be able to perform all the tasks and may have different computational speeds. An equivalent problem can be found in operations research, and it is known as scheduling tasks on unrelated parallel machines (also known as R?Cmax). Given this equivalence observation, we present the spanning tree decentralized task distribution algorithm (ST-DTDA), the first decentralized solution to R?Cmax. ST-DTDA achieves decomposition by means of the min?max algorithm, a member of the generalized distributive law family, that performs inference by message-passing along the edges of a graphical model (known as a junction tree). Specifically, ST-DTDA uses min?max to optimally solve an approximation of the original R?Cmax problem that results from eliminating possible agent-task allocations until it is mapped into an acyclic structure. To eliminate those allocations that are least likely to have an impact on the solution quality, ST-DTDA uses a heuristic approach. Moreover, ST-DTDA provides a per-instance approximation ratio that guarantees that the makespan of its solution (optimal in the approximated R?Cmax problem) is not more than a factor ensuremathrho times the makespan of the optimal of the original problem. In our empirical evaluation of ST-DTDA, we show that ST-DTDA, with a min-regret heuristic, converges to solutions that are between 78 and 95% optimal whilst providing approximation ratios lower than 3.
128.
Fischer, J. E.; Jiang, W; Kerne, A; Greenhalgh, C; Ramchurn, Sarvapali D; Reece, Steven; Pantidi, N; Rodden, T
Supporting Team Coordination on the Ground: Requirements from a Mixed Reality Game. Proceedings Article
In: 11th Int. Conference on the Design of Cooperative Systems (COOP ?14), 2014.
@inproceedings{orchid192,
title = {Supporting Team Coordination on the Ground: Requirements from a Mixed Reality Game.},
author = {J. E. Fischer and W Jiang and A Kerne and C Greenhalgh and Sarvapali D Ramchurn and Steven Reece and N Pantidi and T Rodden},
year = {2014},
date = {2014-01-01},
booktitle = {11th Int. Conference on the Design of Cooperative Systems (COOP ?14)},
howpublished = {http://www.orchid.ac.uk/eprints/192/1/COOP2014-Fischer-author-version.pdf},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
129.
Jiang, W; Fischer, J. E.; Greenhalgh, C; Ramchurn, Sarvapali D; Wu, Feng; Jennings, Nicholas R; Rodden, T
Social Implications of Agent-based Planning Support for Human Teams. Proceedings Article
In: 2014 Int. Conference on Collaboration Technologies and Systems, 2014.
@inproceedings{orchid191,
title = {Social Implications of Agent-based Planning Support for Human Teams.},
author = {W Jiang and J. E. Fischer and C Greenhalgh and Sarvapali D Ramchurn and Feng Wu and Nicholas R Jennings and T Rodden},
year = {2014},
date = {2014-01-01},
booktitle = {2014 Int. Conference on Collaboration Technologies and Systems},
howpublished = {http://www.orchid.ac.uk/eprints/191/1/CTS2014-Jiang-author-version.pdf},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
130.
Pawlowski, Krzysztof; Kurach, Karol; Svensson, Kim; Ramchurn, Sarvapali D; Michalak, Tomasz; Rahwan, Talal
Coalition Structure Generation with the Graphics Processing Unit Proceedings Article
In: 13th Int. Conf. on Autonomous Agents and Multi-Agent Systems, 2014.
@inproceedings{orchid176,
title = {Coalition Structure Generation with the Graphics Processing Unit},
author = {Krzysztof Pawlowski and Karol Kurach and Kim Svensson and Sarvapali D Ramchurn and Tomasz Michalak and Talal Rahwan},
year = {2014},
date = {2014-01-01},
booktitle = {13th Int. Conf. on Autonomous Agents and Multi-Agent Systems},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
131.
Huynh, Trung Dong; Ebden, Mark; Ramchurn, Sarvapali; Roberts, Stephen; Moreau, Luc
Data quality assessment from provenance graphs Proceedings Article
In: Provenance Analytics 2014, 2014.
@inproceedings{eps365510,
title = {Data quality assessment from provenance graphs},
author = {Trung Dong Huynh and Mark Ebden and Sarvapali Ramchurn and Stephen Roberts and Luc Moreau},
url = {http://eprints.soton.ac.uk/365510/},
year = {2014},
date = {2014-01-01},
booktitle = {Provenance Analytics 2014},
abstract = {Provenance is a domain-independent means to represent what happened in an application, which can help verify data and infer data quality. Provenance patterns can manifest real-world phenomena such as a significant interest in a piece of content, providing an indication of its quality, or even issues such as undesirable interactions within a group of contributors. This paper presents an application-independent methodology for analyzing data based on the network metrics of provenance graphs to learn about such patterns and to relate them to data quality in an automated manner. Validating this method on the provenance records of CollabMap, an online crowdsourcing mapping application, we demonstrated an accuracy level of over 95% for the trust classification of data generated by the crowd therein.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Provenance is a domain-independent means to represent what happened in an application, which can help verify data and infer data quality. Provenance patterns can manifest real-world phenomena such as a significant interest in a piece of content, providing an indication of its quality, or even issues such as undesirable interactions within a group of contributors. This paper presents an application-independent methodology for analyzing data based on the network metrics of provenance graphs to learn about such patterns and to relate them to data quality in an automated manner. Validating this method on the provenance records of CollabMap, an online crowdsourcing mapping application, we demonstrated an accuracy level of over 95% for the trust classification of data generated by the crowd therein.
132.
Jennings, Nicholas R.; Moreau, Luc; Nicholson, D; Ramchurn, Sarvapali D.; Roberts, S; Rodden, T; Rogers, Alex
On human-agent collectives Journal Article
In: Communications of the ACM, vol. 57, no. 12, pp. 33-42, 2014.
@article{eps364593,
title = {On human-agent collectives},
author = {Nicholas R. Jennings and Luc Moreau and D Nicholson and Sarvapali D. Ramchurn and S Roberts and T Rodden and Alex Rogers},
url = {http://eprints.soton.ac.uk/364593/},
year = {2014},
date = {2014-01-01},
journal = {Communications of the ACM},
volume = {57},
number = {12},
pages = {33-42},
abstract = {We live in a world where a host of computer systems, distributed throughout our physical and information environments, are increasingly implicated in our everyday actions. Computer technologies impact all aspects of our lives and our relationship with the digital has fundamentally altered as computers have moved out of the workplace and away from the desktop. Networked computers, tablets, phones and personal devices are now commonplace, as are an increasingly diverse set of digital devices built into the world around us. Data and information is generated at unprecedented speeds and volumes from an increasingly diverse range of sources. It is then combined in unforeseen ways, limited only by human imagination. People?s activities and collaborations are becoming ever more dependent upon and intertwined with this ubiquitous information substrate. As these trends continue apace, it is becoming apparent that many endeavours involve the symbiotic interleaving of humans and computers. Moreover, the emergence of these close-knit partnerships is inducing profound change. Rather than issuing instructions to passive machines that wait until they are asked before doing anything, we will work in tandem with highly inter-connected computational components that act autonomously and intelligently (aka agents). As a consequence, greater attention needs to be given to the balance of control between people and machines. In many situations, humans will be in charge and agents will predominantly act in a supporting role. In other cases, however, the agents will be in control and humans will play the supporting role. We term this emerging class of systems human-agent collectives (HACs) to reflect the close partnership and the flexible social interactions between the humans and the computers. As well as exhibiting increased autonomy, such systems will be inherently open and social. This means the participants will need to continually and flexibly establish and manage a range of social relationships. Thus, depending on the task at hand, different constellations of people, resources, and information will need to come together, operate in a coordinated fashion, and then disband. The openness and presence of many distinct stakeholders means participation will be motivated by a broad range of incentives rather than diktat. This article outlines the key research challenges involved in developing a comprehensive understanding of HACs. To illuminate this agenda, a nascent application in the domain of disaster response is presented.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We live in a world where a host of computer systems, distributed throughout our physical and information environments, are increasingly implicated in our everyday actions. Computer technologies impact all aspects of our lives and our relationship with the digital has fundamentally altered as computers have moved out of the workplace and away from the desktop. Networked computers, tablets, phones and personal devices are now commonplace, as are an increasingly diverse set of digital devices built into the world around us. Data and information is generated at unprecedented speeds and volumes from an increasingly diverse range of sources. It is then combined in unforeseen ways, limited only by human imagination. People?s activities and collaborations are becoming ever more dependent upon and intertwined with this ubiquitous information substrate. As these trends continue apace, it is becoming apparent that many endeavours involve the symbiotic interleaving of humans and computers. Moreover, the emergence of these close-knit partnerships is inducing profound change. Rather than issuing instructions to passive machines that wait until they are asked before doing anything, we will work in tandem with highly inter-connected computational components that act autonomously and intelligently (aka agents). As a consequence, greater attention needs to be given to the balance of control between people and machines. In many situations, humans will be in charge and agents will predominantly act in a supporting role. In other cases, however, the agents will be in control and humans will play the supporting role. We term this emerging class of systems human-agent collectives (HACs) to reflect the close partnership and the flexible social interactions between the humans and the computers. As well as exhibiting increased autonomy, such systems will be inherently open and social. This means the participants will need to continually and flexibly establish and manage a range of social relationships. Thus, depending on the task at hand, different constellations of people, resources, and information will need to come together, operate in a coordinated fashion, and then disband. The openness and presence of many distinct stakeholders means participation will be motivated by a broad range of incentives rather than diktat. This article outlines the key research challenges involved in developing a comprehensive understanding of HACs. To illuminate this agenda, a nascent application in the domain of disaster response is presented.
133.
Bistaffa, Filippo; Farinelli, Alessandro; Cerquides, Jesus; Rodriguez-Aguilar, Juan Antonio; Ramchurn, Sarvapali D
Anytime Coalition Structure Generation on Synergy Graphs Proceedings Article
In: 13th Int. Conf. on Autonomous Agents and Multi-Agent Systems, pp. 13-20, 2014.
@inproceedings{orchid175,
title = {Anytime Coalition Structure Generation on Synergy Graphs},
author = {Filippo Bistaffa and Alessandro Farinelli and Jesus Cerquides and Juan Antonio Rodriguez-Aguilar and Sarvapali D Ramchurn},
url = {http://aamas2014.lip6.fr/proceedings/aamas/p13.pdf},
year = {2014},
date = {2014-01-01},
booktitle = {13th Int. Conf. on Autonomous Agents and Multi-Agent Systems},
pages = {13-20},
abstract = {We consider the coalition structure generation (CSG) problem on
synergy graphs, which arises in many practical applications where
communication constraints, social or trust relationships must be
taken into account when forming coalitions. We propose a novel
representation of this problem based on the concept of edge contraction,
and an innovative branch and bound approach (CFSS),
which is particularly efficient when applied to a general class of
characteristic functions. This new model provides a non-redundant
partition of the search space, hence allowing an effective parallelisation.
We evaluate CFSS on two benchmark functions, the edge
sum with coordination cost and the collective energy purchasing
functions, comparing its performance with the best algorithm for
CSG on synergy graphs: DyCE. The latter approach is centralised
and cannot be efficiently parallelised due to the exponential memory
requirements in the number of agents, which limits its scalability
(while CFSS memory requirements are only polynomial).
Our results show that, when the graphs are very sparse, CFSS is
4 orders of magnitude faster than DyCE. Moreover, CFSS is the
first approach to provide anytime approximate solutions with quality
guarantees for very large systems (i.e., with more than 2700
agents).},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We consider the coalition structure generation (CSG) problem on
synergy graphs, which arises in many practical applications where
communication constraints, social or trust relationships must be
taken into account when forming coalitions. We propose a novel
representation of this problem based on the concept of edge contraction,
and an innovative branch and bound approach (CFSS),
which is particularly efficient when applied to a general class of
characteristic functions. This new model provides a non-redundant
partition of the search space, hence allowing an effective parallelisation.
We evaluate CFSS on two benchmark functions, the edge
sum with coordination cost and the collective energy purchasing
functions, comparing its performance with the best algorithm for
CSG on synergy graphs: DyCE. The latter approach is centralised
and cannot be efficiently parallelised due to the exponential memory
requirements in the number of agents, which limits its scalability
(while CFSS memory requirements are only polynomial).
Our results show that, when the graphs are very sparse, CFSS is
4 orders of magnitude faster than DyCE. Moreover, CFSS is the
first approach to provide anytime approximate solutions with quality
guarantees for very large systems (i.e., with more than 2700
agents).
synergy graphs, which arises in many practical applications where
communication constraints, social or trust relationships must be
taken into account when forming coalitions. We propose a novel
representation of this problem based on the concept of edge contraction,
and an innovative branch and bound approach (CFSS),
which is particularly efficient when applied to a general class of
characteristic functions. This new model provides a non-redundant
partition of the search space, hence allowing an effective parallelisation.
We evaluate CFSS on two benchmark functions, the edge
sum with coordination cost and the collective energy purchasing
functions, comparing its performance with the best algorithm for
CSG on synergy graphs: DyCE. The latter approach is centralised
and cannot be efficiently parallelised due to the exponential memory
requirements in the number of agents, which limits its scalability
(while CFSS memory requirements are only polynomial).
Our results show that, when the graphs are very sparse, CFSS is
4 orders of magnitude faster than DyCE. Moreover, CFSS is the
first approach to provide anytime approximate solutions with quality
guarantees for very large systems (i.e., with more than 2700
agents).
134.
Alam, Muddasser; Alan, Alper; Rogers, Alex; Ramchurn, Sarvapali D.
Towards a smart home framework Proceedings Article
In: 5th ACM Workshop On Embedded Systems For Energy-Efficient Buildings (BuildSys2013), 2013.
@inproceedings{eps357187,
title = {Towards a smart home framework},
author = {Muddasser Alam and Alper Alan and Alex Rogers and Sarvapali D. Ramchurn},
url = {http://eprints.soton.ac.uk/357187/},
year = {2013},
date = {2013-01-01},
booktitle = {5th ACM Workshop On Embedded Systems For Energy-Efficient Buildings (BuildSys2013)},
abstract = {We present our Smart Home Framework (SHF) which simplifies the modelling, prototyping and simulation of smart infrastructure (i.e., smart home and smart communities). It provides the buildings blocks (e.g., home appliances) that can be extended and assembled together to build a smart infrastructure model to which appropriate AI techniques can be applied. This approach enables rapid modelling where new research initiatives can build on existing work.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We present our Smart Home Framework (SHF) which simplifies the modelling, prototyping and simulation of smart infrastructure (i.e., smart home and smart communities). It provides the buildings blocks (e.g., home appliances) that can be extended and assembled together to build a smart infrastructure model to which appropriate AI techniques can be applied. This approach enables rapid modelling where new research initiatives can build on existing work.
135.
Alam, Muddasser; Ramchurn, Sarvapali; Rogers, Alex
Cooperative energy exchange for the efficient use of energy and resources in remote communities. [Winner, Best Student Paper Award at AAMAS2013] Proceedings Article
In: Twelfth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2013), 2013.
@inproceedings{eps346637,
title = {Cooperative energy exchange for the efficient use of energy and resources in remote communities. [Winner, Best Student Paper Award at AAMAS2013]},
author = {Muddasser Alam and Sarvapali Ramchurn and Alex Rogers},
url = {http://eprints.soton.ac.uk/346637/},
year = {2013},
date = {2013-01-01},
booktitle = {Twelfth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2013)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
136.
Alam, Muddasser; Rogers, Alex; Ramchurn, Sarvapali
Interdependent multi-issue negotiation for energy exchange in remote communities Proceedings Article
In: Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13), 2013.
@inproceedings{eps350941,
title = {Interdependent multi-issue negotiation for energy exchange in remote communities},
author = {Muddasser Alam and Alex Rogers and Sarvapali Ramchurn},
url = {http://eprints.soton.ac.uk/350941/},
year = {2013},
date = {2013-01-01},
booktitle = {Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13)},
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 protocol imposes restrictions over negotiation such that it reduces the complex interdependent multi-issue negotiation to one where agents have a strategy profile in subgame perfect Nash equilibrium. We show that our negotiation protocol is tractable, concurrent, scalable and leads to Pareto-optimal outcomes in a decentralised manner. We empirically evaluate our protocol and show that, in this instance, a society of agents can (i) improve the overall utilities by 14% and (ii) reduce their overall use of the batteries by 37%},
keywords = {},
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 protocol imposes restrictions over negotiation such that it reduces the complex interdependent multi-issue negotiation to one where agents have a strategy profile in subgame perfect Nash equilibrium. We show that our negotiation protocol is tractable, concurrent, scalable and leads to Pareto-optimal outcomes in a decentralised manner. We empirically evaluate our protocol and show that, in this instance, a society of agents can (i) improve the overall utilities by 14% and (ii) reduce their overall use of the batteries by 37%
137.
Alam, Muddasser; Rogers, Alex; Ramchurn, Sarvapali D.
Interdependent multi-issue negotiation for energy exchange in remote communities Proceedings Article
In: International Workshop on AI Problems and Approaches for Intelligent Environments (AI4IE), 2013.
@inproceedings{eps357186,
title = {Interdependent multi-issue negotiation for energy exchange in remote communities},
author = {Muddasser Alam and Alex Rogers and Sarvapali D. Ramchurn},
url = {http://eprints.soton.ac.uk/357186/},
year = {2013},
date = {2013-01-01},
booktitle = {International Workshop on AI Problems and Approaches for Intelligent Environments (AI4IE)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
138.
Cerquides, Jesus; Farinelli, Alessandro; Meseguer, Pedro; Ramchurn, Sarvapali
A tutorial on optimisation for multi-agent systems Journal Article
In: The Computer Journal, pp. 1–26, 2013.
@article{eps361998,
title = {A tutorial on optimisation for multi-agent systems},
author = {Jesus Cerquides and Alessandro Farinelli and Pedro Meseguer and Sarvapali Ramchurn},
url = {http://eprints.soton.ac.uk/361998/},
year = {2013},
date = {2013-01-01},
journal = {The Computer Journal},
pages = {1–26},
abstract = {Research on optimization in multi-agent systems (MASs) has contributed with a wealth of techniques to solve many of the challenges arising in a wide range of multi-agent application domains. Multi-agent optimization focuses on casting MAS problems into optimization problems. The solving of those problems could possibly involve the active participation of the agents in a MAS. Research on multi-agent optimization has rapidly become a very technical, specialized field. Moreover, the contributions to the field in the literature are largely scattered. These two factors dramatically hinder access to a basic, general view of the foundations of the field. This tutorial is intended to ease such access by providing a gentle introduction to fundamental concepts and techniques on multi-agent optimization},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Research on optimization in multi-agent systems (MASs) has contributed with a wealth of techniques to solve many of the challenges arising in a wide range of multi-agent application domains. Multi-agent optimization focuses on casting MAS problems into optimization problems. The solving of those problems could possibly involve the active participation of the agents in a MAS. Research on multi-agent optimization has rapidly become a very technical, specialized field. Moreover, the contributions to the field in the literature are largely scattered. These two factors dramatically hinder access to a basic, general view of the foundations of the field. This tutorial is intended to ease such access by providing a gentle introduction to fundamental concepts and techniques on multi-agent optimization
139.
Farinelli, Alessandro; Bicego, Manuele; Ramchurn, Sarvapali; Zuchelli, Marco
C-Link: a hierarchical clustering approach to large-scale near-optimal coalition formation Proceedings Article
In: 23rd International Joint Conference on Artificial Intelligence, AAAI Press / International Joint Conferences on Artificial Intelligence, 2013.
@inproceedings{eps351521,
title = {C-Link: a hierarchical clustering approach to large-scale near-optimal coalition formation},
author = {Alessandro Farinelli and Manuele Bicego and Sarvapali Ramchurn and Marco Zuchelli},
url = {http://eprints.soton.ac.uk/351521/},
year = {2013},
date = {2013-01-01},
booktitle = {23rd International Joint Conference on Artificial Intelligence},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
abstract = {Coalition formation is a fundamental approach to multi-agent coordination. In this paper we address the specific problem of coalition structure generation, and focus on providing good-enough solutions using a novel heuristic approach that is based on data clustering methods. In particular, we propose a hierarchical agglomerative clustering approach (C-Link), which uses a similarity criterion between coalitions based on the gain that the system achieves if two coalitions merge. We empirically evaluate C-Link on a synthetic benchmark data-set as well as in collective energy purchasing settings. Our results show that the C-link approach performs very well against an optimal benchmark based on Mixed-Integer Programming, achieving solutions which are in the worst case about 80% of the optimal (in the synthetic data-set), and 98% of the optimal (in the energy data-set). Thus we show that C-Link can return solutions for problems involving thousands of agents within minutes.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Coalition formation is a fundamental approach to multi-agent coordination. In this paper we address the specific problem of coalition structure generation, and focus on providing good-enough solutions using a novel heuristic approach that is based on data clustering methods. In particular, we propose a hierarchical agglomerative clustering approach (C-Link), which uses a similarity criterion between coalitions based on the gain that the system achieves if two coalitions merge. We empirically evaluate C-Link on a synthetic benchmark data-set as well as in collective energy purchasing settings. Our results show that the C-link approach performs very well against an optimal benchmark based on Mixed-Integer Programming, achieving solutions which are in the worst case about 80% of the optimal (in the synthetic data-set), and 98% of the optimal (in the energy data-set). Thus we show that C-Link can return solutions for problems involving thousands of agents within minutes.
140.
Fischer, Joel E.; Ramchurn, Sarvapali D.; Osborne, Michael A.; Parson, Oliver; Huynh, Trung Dong; Alam, Muddasser; Pantidi, Nadia; Moran, Stuart; Bachour, Khaled; Reece, Steven; Costanza, Enrico; Rodden, Tom; Jennings, Nicholas R.
Recommending Energy Tariffs and Load Shifting Based on Smart Household Usage Profiling Proceedings Article
In: International Conference on Intelligent User Interfaces, pp. 383–394, 2013.
@inproceedings{eps346991,
title = {Recommending Energy Tariffs and Load Shifting Based on Smart Household Usage Profiling},
author = {Joel E. Fischer and Sarvapali D. Ramchurn and Michael A. Osborne and Oliver Parson and Trung Dong Huynh and Muddasser Alam and Nadia Pantidi and Stuart Moran and Khaled Bachour and Steven Reece and Enrico Costanza and Tom Rodden and Nicholas R. Jennings},
url = {http://eprints.soton.ac.uk/346991/},
year = {2013},
date = {2013-01-01},
booktitle = {International Conference on Intelligent User Interfaces},
pages = {383–394},
abstract = {We present a system and study of personalized energy-related recommendation. AgentSwitch utilizes electricity usage data collected from users' households over a period of time to realize a range of smart energy-related recommendations on energy tariffs, load detection and usage shifting. The web service is driven by a third party real-time energy tariff API (uSwitch), an energy data store, a set of algorithms for usage prediction, and appliance-level load disaggregation. We present the system design and user evaluation consisting of interviews and interface walkthroughs. We recruited participants from a previous study during which three months of their household's energy use was recorded to evaluate personalized recommendations in AgentSwitch. Our contributions are a) a systems architecture for personalized energy services; and b) findings from the evaluation that reveal challenges in designing energy-related recommender systems. In response to the challenges we formulate design recommendations to mitigate barriers to switching tariffs, to incentivize load shifting, and to automate energy management.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We present a system and study of personalized energy-related recommendation. AgentSwitch utilizes electricity usage data collected from users' households over a period of time to realize a range of smart energy-related recommendations on energy tariffs, load detection and usage shifting. The web service is driven by a third party real-time energy tariff API (uSwitch), an energy data store, a set of algorithms for usage prediction, and appliance-level load disaggregation. We present the system design and user evaluation consisting of interviews and interface walkthroughs. We recruited participants from a previous study during which three months of their household's energy use was recorded to evaluate personalized recommendations in AgentSwitch. Our contributions are a) a systems architecture for personalized energy services; and b) findings from the evaluation that reveal challenges in designing energy-related recommender systems. In response to the challenges we formulate design recommendations to mitigate barriers to switching tariffs, to incentivize load shifting, and to automate energy management.
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}
}
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}
}
Sorry, no publications matched your criteria.