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181.
Espinoza, Fredrik; Roure, David De; Hamfors, Ola; Hinz, Lucas; Holmberg, Jesper; Jansson, Carl-Gustaf; Jennings, Nick; Luck, Mike; L"onnqvist, Peter; Ramchurn, Sarvapali; Sandin, Anna; Thompson, Mark; Bylund, Markus
Intrusiveness Management for Focused, Efficient, and Enjoyable Activities Book Section
In: The Disappearing Computer: Interaction Design, System Infrastructures and Applications for Smart Environments, pp. 143–160, Springer, 2007.
@incollection{eps265985,
title = {Intrusiveness Management for Focused, Efficient, and Enjoyable Activities},
author = {Fredrik Espinoza and David De Roure and Ola Hamfors and Lucas Hinz and Jesper Holmberg and Carl-Gustaf Jansson and Nick Jennings and Mike Luck and Peter L"onnqvist and Sarvapali Ramchurn and Anna Sandin and Mark Thompson and Markus Bylund},
url = {http://eprints.soton.ac.uk/265985/},
year = {2007},
date = {2007-01-01},
booktitle = {The Disappearing Computer: Interaction Design, System Infrastructures and Applications for Smart Environments},
pages = {143–160},
publisher = {Springer},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
182.
Rahwan, T.; Ramchurn, S. D.; Dang, V. D.; Jennings, N. R.
Near-optimal anytime coalition structure generation Proceedings Article
In: 20th International Joint Conference on Artificial Intelligence (IJCAI), pp. 2365–2371, 2007.
@inproceedings{eps263074,
title = {Near-optimal anytime coalition structure generation},
author = {T. Rahwan and S. D. Ramchurn and V. D. Dang and N. R. Jennings},
url = {http://eprints.soton.ac.uk/263074/},
year = {2007},
date = {2007-01-01},
booktitle = {20th International Joint Conference on Artificial Intelligence (IJCAI)},
pages = {2365–2371},
abstract = {Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best set of agents that should participate in a given team. To this end, in this paper, we present a novel, anytime algorithms designed for this purpose. Our algorithm can generate solutions that either have a tight bound from the optimal or are optimal (depending on the objective) and works by partitioning the space in terms of a small set of elements that represent structures which contain coalitions of particular sizes. It then performs an online heuristic search that prunes the space and only considers valid and non-redundant coalition structures. We empirically show that we are able to find solutions that are, in the worst case, 99% efficient in 0.0043% of the time to find the optimal value by the state of the art dynamic programming (DP) algorithm (for 20 agents), using 33% less memory.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best set of agents that should participate in a given team. To this end, in this paper, we present a novel, anytime algorithms designed for this purpose. Our algorithm can generate solutions that either have a tight bound from the optimal or are optimal (depending on the objective) and works by partitioning the space in terms of a small set of elements that represent structures which contain coalitions of particular sizes. It then performs an online heuristic search that prunes the space and only considers valid and non-redundant coalition structures. We empirically show that we are able to find solutions that are, in the worst case, 99% efficient in 0.0043% of the time to find the optimal value by the state of the art dynamic programming (DP) algorithm (for 20 agents), using 33% less memory.
183.
Rahwan, Talal; Ramchurn, Sarvapali D.; Dang, Viet D.; Giovannucci, Andrea; Jennings, N. R.
Anytime Optimal Coalition Structure Generation Proceedings Article
In: 22nd Conference on Artificial Intelligence (AAAI), pp. 1184–1190, 2007.
@inproceedings{eps263433,
title = {Anytime Optimal Coalition Structure Generation},
author = {Talal Rahwan and Sarvapali D. Ramchurn and Viet D. Dang and Andrea Giovannucci and N. R. Jennings},
url = {http://eprints.soton.ac.uk/263433/},
year = {2007},
date = {2007-01-01},
booktitle = {22nd Conference on Artificial Intelligence (AAAI)},
pages = {1184–1190},
abstract = {Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best groups of agents to select to achieve some goal. To this end, in this paper, we present a novel, optimal anytime algorithm for this coalition structure generation problem that is significantly faster than previous algorithms designed for this purpose. Specifically, our algorithm can generate solutions by partitioning the space of all potential coalitions into sub-spaces that contain coalition structures that are similar, according to some criterion, such that these sub-spaces can be pruned by identifying their bounds. Using this representation, the algorithm then searches through only valid and unique coalition structures and selects the best among them using a branch-and-bound technique. We empirically show that we are able to find solutions that are optimal in 0.082% of the time taken by the state of the art dynamic programming algorithm (for 27 agents) using much less memory (O(2^ n) instead of O(3^ n) for the set of n agents). Moreover, our algorithm is the first to be able to solve the coalition structure generation problem for numbers of agents bigger than 27 in reasonable time (less than 90 minutes for 27 agents as opposed to around 2 months for the best previous solution).},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best groups of agents to select to achieve some goal. To this end, in this paper, we present a novel, optimal anytime algorithm for this coalition structure generation problem that is significantly faster than previous algorithms designed for this purpose. Specifically, our algorithm can generate solutions by partitioning the space of all potential coalitions into sub-spaces that contain coalition structures that are similar, according to some criterion, such that these sub-spaces can be pruned by identifying their bounds. Using this representation, the algorithm then searches through only valid and unique coalition structures and selects the best among them using a branch-and-bound technique. We empirically show that we are able to find solutions that are optimal in 0.082% of the time taken by the state of the art dynamic programming algorithm (for 27 agents) using much less memory (O(2^ n) instead of O(3^ n) for the set of n agents). Moreover, our algorithm is the first to be able to solve the coalition structure generation problem for numbers of agents bigger than 27 in reasonable time (less than 90 minutes for 27 agents as opposed to around 2 months for the best previous solution).
184.
Ramchurn, S. D.; Sierra, C.; Godo, L.; Jennings, N. R.
Negotiating using rewards. Journal Article
In: Artificial Intelligence Journal., vol. 171, no. 10-15, pp. 805–837, 2007.
@article{eps264225,
title = {Negotiating using rewards.},
author = {S. D. Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/264225/},
year = {2007},
date = {2007-01-01},
journal = {Artificial Intelligence Journal.},
volume = {171},
number = {10-15},
pages = {805–837},
abstract = {Negotiation is a fundamental interaction mechanism in multi-agent systems because it allows self-interested agents to come to mutually beneficial agreements and partition resources efficiently and effectively. Now, in many situations, the agents need to negotiate with one another many times and so developing strategies that are effective over repeated interactions is an important challenge. Against this background, a growing body of work has examined the use of Persuasive Negotiation (PN), which involves negotiating using rhetorical arguments (such as threats, rewards, or appeals), in trying to convince an opponent to accept a given offer. Such mechanisms are especially suited to repeated encounters because they allow agents to influence the outcomes of future negotiations, while negotiating a deal in the present one, with the aim of producing results that are beneficial to both parties. To this end, in this paper, we develop a comprehensive PN mechanism for repeated interactions that makes use of rewards that can be asked for or given to. Our mechanism consists of two parts. First, a novel protocol that structures the interaction by capturing the commitments that agents incur when using rewards. Second, a new reward generation algorithm that constructs promises of rewards in future interactions as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. We then go on to develop a specific negotiation tactic, based on this reward generation algorithm, and show that it can achieve significantly better outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation in a Multi-Move Prisoners? dilemma setting, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Negotiation is a fundamental interaction mechanism in multi-agent systems because it allows self-interested agents to come to mutually beneficial agreements and partition resources efficiently and effectively. Now, in many situations, the agents need to negotiate with one another many times and so developing strategies that are effective over repeated interactions is an important challenge. Against this background, a growing body of work has examined the use of Persuasive Negotiation (PN), which involves negotiating using rhetorical arguments (such as threats, rewards, or appeals), in trying to convince an opponent to accept a given offer. Such mechanisms are especially suited to repeated encounters because they allow agents to influence the outcomes of future negotiations, while negotiating a deal in the present one, with the aim of producing results that are beneficial to both parties. To this end, in this paper, we develop a comprehensive PN mechanism for repeated interactions that makes use of rewards that can be asked for or given to. Our mechanism consists of two parts. First, a novel protocol that structures the interaction by capturing the commitments that agents incur when using rewards. Second, a new reward generation algorithm that constructs promises of rewards in future interactions as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. We then go on to develop a specific negotiation tactic, based on this reward generation algorithm, and show that it can achieve significantly better outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation in a Multi-Move Prisoners? dilemma setting, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this.
185.
Rogers, Alex; Dash, Rajdeep K.; Ramchurn, Sarvapali D.; Vytelingum, Perukrishnen; Jennings, N. R.
Coordinating Team Players within a Noisy Iterated Prisoner?s Dilemma Tournament Journal Article
In: Theoretical Computer Science, vol. 377, no. 1-3, pp. 243–259, 2007.
@article{eps263238,
title = {Coordinating Team Players within a Noisy Iterated Prisoner?s Dilemma Tournament},
author = {Alex Rogers and Rajdeep K. Dash and Sarvapali D. Ramchurn and Perukrishnen Vytelingum and N. R. Jennings},
url = {http://eprints.soton.ac.uk/263238/},
year = {2007},
date = {2007-01-01},
journal = {Theoretical Computer Science},
volume = {377},
number = {1-3},
pages = {243–259},
abstract = {In this paper, we present our investigation into the use of a team of players within a noisy Iterated Prisoner?s Dilemma (IPD) tournament. We show that the members of such a team are able to use a pre-arranged sequence of moves that they make at the start of each interaction in order to recognise one another, and that by coordinating their actions they can increase the chances that one of the team members wins the round-robin style tournament. We consider, in detail, the factors that influence the performance of this team and we show that the problem that the team members face, when they attempt to recognise one another within the noisy IPD tournament, is exactly analogous to the problem, studied in information theory, of communicating reliably over a noisy channel. Thus we demonstrate that we can use error correcting codes to implement this recognition, and by doing so, further optimise the performance of the team.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In this paper, we present our investigation into the use of a team of players within a noisy Iterated Prisoner?s Dilemma (IPD) tournament. We show that the members of such a team are able to use a pre-arranged sequence of moves that they make at the start of each interaction in order to recognise one another, and that by coordinating their actions they can increase the chances that one of the team members wins the round-robin style tournament. We consider, in detail, the factors that influence the performance of this team and we show that the problem that the team members face, when they attempt to recognise one another within the noisy IPD tournament, is exactly analogous to the problem, studied in information theory, of communicating reliably over a noisy channel. Thus we demonstrate that we can use error correcting codes to implement this recognition, and by doing so, further optimise the performance of the team.
186.
Rogers, Alex; Dash, Rajdeep K.; Ramchurn, Sarvapali D.; Vytelingum, Perukrishnen; Jennings, N. R.
Error-Correcting Codes for Team Coordination within a Noisy Iterated Prisoner?s Dilemma Tournament Book Section
In: Kendel, Graham; Yao, Xin; Chong, Siang Yew (Ed.): The Iterated Prisoners Dilemma Competition: Celebrating the 20th Anniversary, pp. 205–229, World Scientific, 2007.
@incollection{eps263264,
title = {Error-Correcting Codes for Team Coordination within a Noisy Iterated Prisoner?s Dilemma Tournament},
author = {Alex Rogers and Rajdeep K. Dash and Sarvapali D. Ramchurn and Perukrishnen Vytelingum and N. R. Jennings},
editor = {Graham Kendel and Xin Yao and Siang Yew Chong},
url = {http://eprints.soton.ac.uk/263264/},
year = {2007},
date = {2007-01-01},
booktitle = {The Iterated Prisoners Dilemma Competition: Celebrating the 20th Anniversary},
pages = {205–229},
publisher = {World Scientific},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
187.
Karunatillake, N. C.; Jennings, N. R.; Rahwan, I.; Ramchurn, S. D.
Managing Social Influences through Argumentation-Based Negotiation Proceedings Article
In: Third International Workshop on Argumentation in Multi-Agent Systems (ArgMAS 2006), pp. 35–52, 2006, (Event Dates: 8th May 2006).
@inproceedings{eps262022,
title = {Managing Social Influences through Argumentation-Based Negotiation},
author = {N. C. Karunatillake and N. R. Jennings and I. Rahwan and S. D. Ramchurn},
url = {http://eprints.soton.ac.uk/262022/},
year = {2006},
date = {2006-01-01},
booktitle = {Third International Workshop on Argumentation in Multi-Agent Systems (ArgMAS 2006)},
pages = {35–52},
abstract = {Social influences play an important part in the actions that an individual agent may perform within a multi-agent society. However, the incomplete knowledge and the diverse and conflicting influences present within such societies, may stop an agent from abiding by all its social influences. This may, in turn, lead to conflicts that the agents need to identify, manage, and resolve in order for the society to behave in a coherent manner. To this end, we present an empirical study of an argumentation-based negotiation (ABN) approach that allows the agents to detect such conflicts, and then manage and resolve them through the use of argumentative dialogues. To test our theory, we map our ABN model to a multi-agent task allocation scenario. Our results show that using an argumentation approach allows agents to both efficiently and effectively manage their social influences even under high degrees of incompleteness. Finally, we show that allowing agents to argue and resolve such conflicts early in the negotiation encounter increases their efficiency in managing social influences.},
note = {Event Dates: 8th May 2006},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Social influences play an important part in the actions that an individual agent may perform within a multi-agent society. However, the incomplete knowledge and the diverse and conflicting influences present within such societies, may stop an agent from abiding by all its social influences. This may, in turn, lead to conflicts that the agents need to identify, manage, and resolve in order for the society to behave in a coherent manner. To this end, we present an empirical study of an argumentation-based negotiation (ABN) approach that allows the agents to detect such conflicts, and then manage and resolve them through the use of argumentative dialogues. To test our theory, we map our ABN model to a multi-agent task allocation scenario. Our results show that using an argumentation approach allows agents to both efficiently and effectively manage their social influences even under high degrees of incompleteness. Finally, we show that allowing agents to argue and resolve such conflicts early in the negotiation encounter increases their efficiency in managing social influences.
188.
Ramchurn, S. D.; Sierra, C.; Godo, L.; Jennings, N. R.
Negotiating using rewards Proceedings Article
In: 5th Int. Conf. on Autonomous Agents and Multi-Agent Systems, pp. 400–407, 2006.
@inproceedings{eps262591,
title = {Negotiating using rewards},
author = {S. D. Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/262591/},
year = {2006},
date = {2006-01-01},
booktitle = {5th Int. Conf. on Autonomous Agents and Multi-Agent Systems},
journal = {Proc. 5th Int. Conf. on Autonomous Agents and Multi-Agent Systems, Hakodate, Japan},
pages = {400–407},
abstract = {In situations where self-interested agents interact repeatedly, it is important that they are endowed with negotiation techniques that enable them to reach agreements that are profitable in the long run. To this end, we devise a novel negotiation algorithm that generates promises of rewards in future interactions, as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. Moreover, we thus develop a specific negotiation tactic based on this reward generation algorithm and show that it can achieve significantly bettter outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this under concrete settings.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In situations where self-interested agents interact repeatedly, it is important that they are endowed with negotiation techniques that enable them to reach agreements that are profitable in the long run. To this end, we devise a novel negotiation algorithm that generates promises of rewards in future interactions, as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. Moreover, we thus develop a specific negotiation tactic based on this reward generation algorithm and show that it can achieve significantly bettter outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this under concrete settings.
189.
Ashri, R.; Ramchurn, S. D.; Sabater, J.; Luck, M.; Jennings, N. R.
Trust evaluation through relationship analysis Proceedings Article
In: 4th Int Joint Conf. on Autonomous Agents and Multi-Agent Systems, pp. 1005–1011, 2005.
@inproceedings{eps260806,
title = {Trust evaluation through relationship analysis},
author = {R. Ashri and S. D. Ramchurn and J. Sabater and M. Luck and N. R. Jennings},
url = {http://eprints.soton.ac.uk/260806/},
year = {2005},
date = {2005-01-01},
booktitle = {4th Int Joint Conf. on Autonomous Agents and Multi-Agent Systems},
journal = {Proceedings: 4th International Joint Conference on Autonomous Agents and Multi-Agent Systems},
pages = {1005–1011},
abstract = {Current mechanisms for evaluating the trustworthiness of an agent within an electronic marketplace depend either on using a history of interactions or on recommendations from other agents. In the first case, these requirements limit what an agent with no prior interaction history can do. In the second case, they transform the problem into one of trusting the recommending agent. However, these mechanisms do not consider the relationships between agents that arise through interactions (such as buying or selling) or through overarching organisational structures (such as hierarchical or flat), which can also aid in evaluating trustworthiness. In response, this paper outlines a method that enables agents to evaluate the trustworthiness of their counterparts, based solely on an analysis of such relationships. Specifically, relationships are identified using a generic technique in conjunction with a basic model for agentbased marketplaces. They are then interpreted through a trust model that enables the inference of trust valuations based on the different types of relationships. In this way, we provide a further component for a trust evaluation model that addresses some of the limitations of existing work.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Current mechanisms for evaluating the trustworthiness of an agent within an electronic marketplace depend either on using a history of interactions or on recommendations from other agents. In the first case, these requirements limit what an agent with no prior interaction history can do. In the second case, they transform the problem into one of trusting the recommending agent. However, these mechanisms do not consider the relationships between agents that arise through interactions (such as buying or selling) or through overarching organisational structures (such as hierarchical or flat), which can also aid in evaluating trustworthiness. In response, this paper outlines a method that enables agents to evaluate the trustworthiness of their counterparts, based solely on an analysis of such relationships. Specifically, relationships are identified using a generic technique in conjunction with a basic model for agentbased marketplaces. They are then interpreted through a trust model that enables the inference of trust valuations based on the different types of relationships. In this way, we provide a further component for a trust evaluation model that addresses some of the limitations of existing work.
190.
Blankenburg, B.; Dash, R. K.; Ramchurn, S. D.; Klusch, M.; Jennings, N. R.
Trusted kernel-based coalition formation Proceedings Article
In: Proc. 4th Int Joint Conf on Autonomous Agents and Multi-Agent Systems, pp. 989–996, 2005.
@inproceedings{eps260808,
title = {Trusted kernel-based coalition formation},
author = {B. Blankenburg and R. K. Dash and S. D. Ramchurn and M. Klusch and N. R. Jennings},
url = {http://eprints.soton.ac.uk/260808/},
year = {2005},
date = {2005-01-01},
booktitle = {Proc. 4th Int Joint Conf on Autonomous Agents and Multi-Agent Systems},
journal = {Proceedings: 4th International Joint Conference on Autonomous Agents and Multi-agent Systems},
pages = {989–996},
abstract = {We define Trusted Kernel-based Coalition Formation as a novel extension to the traditional kernel-based coalition formation process which ensures agents choose the most reliable coalition partners and are guaranteed to obtain the payment they deserve. To this end, we develop an encryption-based communication protocol and a payment scheme which ensure that agents cannot manipulate the mechanism to their own benefit. Moreover, we integrate a generic trust model in the coalition formation process that permits the selection of the most reliable agents over repeated coalition games. We empirically evaluate our mechanism when iterated and show that, in the long run, it always chooses the coalition structure that has the maximum expected value and determines the payoffs that match their level of reliability.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We define Trusted Kernel-based Coalition Formation as a novel extension to the traditional kernel-based coalition formation process which ensures agents choose the most reliable coalition partners and are guaranteed to obtain the payment they deserve. To this end, we develop an encryption-based communication protocol and a payment scheme which ensure that agents cannot manipulate the mechanism to their own benefit. Moreover, we integrate a generic trust model in the coalition formation process that permits the selection of the most reliable agents over repeated coalition games. We empirically evaluate our mechanism when iterated and show that, in the long run, it always chooses the coalition structure that has the maximum expected value and determines the payoffs that match their level of reliability.
191.
Ramchurn, S. D.; Jennings, N. R.
Trust in agent-based software Book Section
In: Mansell, R.; Collins, B. S. (Ed.): Trust and Crime in Information Societies, pp. 165–204, Elgar Publishing, 2005.
@incollection{eps260823,
title = {Trust in agent-based software},
author = {S. D. Ramchurn and N. R. Jennings},
editor = {R. Mansell and B. S. Collins},
url = {http://eprints.soton.ac.uk/260823/},
year = {2005},
date = {2005-01-01},
booktitle = {Trust and Crime in Information Societies},
pages = {165–204},
publisher = {Elgar Publishing},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
192.
Dash, R. K.; Ramchurn, S. D.; Jennings, N. R.
Trust-Based Mechanism Design Proceedings Article
In: 3rd Int. Conf. on Autonomous Agents and Multi-Agent Systems, pp. 748–755, 2004, (Event Dates: 19-23 July 2004).
@inproceedings{eps259352,
title = {Trust-Based Mechanism Design},
author = {R. K. Dash and S. D. Ramchurn and N. R. Jennings},
url = {http://eprints.soton.ac.uk/259352/},
year = {2004},
date = {2004-01-01},
booktitle = {3rd Int. Conf. on Autonomous Agents and Multi-Agent Systems},
pages = {748–755},
abstract = {We define trust-based mechanism design as an augmentation of traditional mechanism design in which agents take into account the degree of trust that they have in their counterparts when determining their allocations. To this end, we develop an efficient, individually rational, and incentive compatible mechanism based on trust. This mechanism is embedded in a task allocation scenario in which the trust in an agent is derived from the reported performance success of that agent by all the other agents in the system. We also empirically study the evolution of our mechanism when iterated and show that, in the long run, it always chooses the most successful and cheapest agents to fulfill an allocation and chooses better allocations than other comparable models when faced with biased reporting.},
note = {Event Dates: 19-23 July 2004},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We define trust-based mechanism design as an augmentation of traditional mechanism design in which agents take into account the degree of trust that they have in their counterparts when determining their allocations. To this end, we develop an efficient, individually rational, and incentive compatible mechanism based on trust. This mechanism is embedded in a task allocation scenario in which the trust in an agent is derived from the reported performance success of that agent by all the other agents in the system. We also empirically study the evolution of our mechanism when iterated and show that, in the long run, it always chooses the most successful and cheapest agents to fulfill an allocation and chooses better allocations than other comparable models when faced with biased reporting.
193.
Ramchurn, S. D.; Deitch, B.; Thompson, M. K.; Roure, D. C.; Jennings, N. R.; Luck, M.
Minimising intrusiveness in pervasive computing environments using multi-agent negotiation Proceedings Article
In: First Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous'04), pp. 364–372, IEEE, 2004, (Event Dates: August 22 - 26, 2004).
@inproceedings{eps259566,
title = {Minimising intrusiveness in pervasive computing environments using multi-agent negotiation},
author = {S. D. Ramchurn and B. Deitch and M. K. Thompson and D. C. Roure and N. R. Jennings and M. Luck},
url = {http://eprints.soton.ac.uk/259566/},
year = {2004},
date = {2004-01-01},
booktitle = {First Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous'04)},
pages = {364–372},
publisher = {IEEE},
abstract = {This paper highlights intrusiveness as a key issue in the field of pervasive computing environments and presents a multi-agent approach to tackling it. Specifically, we discuss how interruptions can impact on individual and group tasks and how they can be managed by taking into account user and group preferences through negotiation between software agents. The system we develop is implemented on the Jabber platform and is deployed in the context of a meeting room scenario.},
note = {Event Dates: August 22 - 26, 2004},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper highlights intrusiveness as a key issue in the field of pervasive computing environments and presents a multi-agent approach to tackling it. Specifically, we discuss how interruptions can impact on individual and group tasks and how they can be managed by taking into account user and group preferences through negotiation between software agents. The system we develop is implemented on the Jabber platform and is deployed in the context of a meeting room scenario.
194.
Ramchurn, S. D.; Huynh, T. D.; Jennings, N. R.
Trust in Multiagent Systems Journal Article
In: The Knowledge Engineering Review, vol. 19, no. 1, pp. 1–25, 2004.
@article{eps259564,
title = {Trust in Multiagent Systems},
author = {S. D. Ramchurn and T. D. Huynh and N. R. Jennings},
url = {http://eprints.soton.ac.uk/259564/},
year = {2004},
date = {2004-01-01},
journal = {The Knowledge Engineering Review},
volume = {19},
number = {1},
pages = {1–25},
abstract = {Trust is a fundamental concern in large-scale open distributed systems. It lies at the core of all interactions between the entities that have to operate in such uncertain and constantly changing environments. Given this complexity, these components, and the ensuing system, are increasingly being conceptualised, designed, and built using agent-based techniques and, to this end, this paper examines the specific role of trust in multi-agent systems. In particular, we survey the state of the art and provide an account of the main directions along which research efforts are being focused. In so doing, we critically evaluate the relative strengths and weaknesses of the main models that have been proposed and show how, fundamentally, they all seek to minimise the uncertainty in interactions. Finally, we outline the areas that require further research in order to develop a comprehensive treatment of trust in complex computational settings.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Trust is a fundamental concern in large-scale open distributed systems. It lies at the core of all interactions between the entities that have to operate in such uncertain and constantly changing environments. Given this complexity, these components, and the ensuing system, are increasingly being conceptualised, designed, and built using agent-based techniques and, to this end, this paper examines the specific role of trust in multi-agent systems. In particular, we survey the state of the art and provide an account of the main directions along which research efforts are being focused. In so doing, we critically evaluate the relative strengths and weaknesses of the main models that have been proposed and show how, fundamentally, they all seek to minimise the uncertainty in interactions. Finally, we outline the areas that require further research in order to develop a comprehensive treatment of trust in complex computational settings.
195.
Ramchurn, Sarvapali
Multi-Agent Negotiation using Trust and Persuasion PhD Thesis
University of Southampton, 2004.
@phdthesis{eps260200,
title = {Multi-Agent Negotiation using Trust and Persuasion},
author = {Sarvapali Ramchurn},
url = {http://eprints.soton.ac.uk/260200/},
year = {2004},
date = {2004-01-01},
school = {University of Southampton},
abstract = {In this thesis, we propose a panoply of tools and techniques to manage inter-agent dependencies in open, distributed multi-agent systems that have significant degrees of uncertainty. In particular, we focus on situations in which agents are involved in repeated interactions where they need to negotiate to resolve conflicts that may arise between them. To this end, we endow agents with decision making models that exploit the notion of trust and use persuasive techniques during the negotiation process to reduce the level of uncertainty and achieve better deals in the long run. Firstly, we develop and evaluate a new trust model (called CREDIT) that allows agents to measure the degree of trust they should place in their opponents. This model reduces the uncertainty that agents have about their opponents' reliability. Thus, over repeated interactions, CREDIT enables agents to model their opponents' reliability using probabilistic techniques and a fuzzy reasoning mechanism that allows the combination of measures based on reputation (indirect interactions) and confidence (direct interactions). In so doing, CREDIT takes a wider range of behaviour-influencing factors into account than existing models, including the norms of the agents and the institution within which transactions occur. We then explore a novel application of trust models by showing how the measures developed in CREDIT ca be applied negotiations in multiple encounters. Specifically we show that agents that use CREDIT are able to avoid unreliable agents, both during the selection of interaction partners and during the negotiation process itself by using trust to adjust their negotiation stance. Also, we empirically show that agents are able to reach good deals with agents that are unreliable to some degree (rather than completely unreliable) and with those that try to strategically exploit their opponent. Secondly, having applied CREDIT to negotiations, we further extend the application of trust to reduce uncertainty about the reliability of agents in mechanism design (where the honesty of agents is elicited by the protocol). Thus, we develop $backslash$acftbmd that allows agents using a trust model (such as CREDIT) to reach efficient agreements that choose the most reliable agents in the long run. In particular, we show that our mechanism enforces truth-telling from the agents (i.e. it is incentive compatible), both about their perceived reliability of their opponent and their valuations for the goods to be traded. In proving the latter properties, our trust-based mechanism is shown to be the first reputation mechanism that implements individual rationality, incentive compatibility, and efficiency. Our trust-based mechanism is also empirically evaluated and shown to be better than other comparable models in reaching the outcome that maximises all the negotiating agents' utilities and in choosing the most reliable agents in the long run. Thirdly, having explored ways to reduce uncertainties about reliability and honesty, we use persuasive negotiation techniques to tackle issues associated with uncertainties that agents have about the preferences and the space of possible agreements. To this end, we propose a novel protocol and reasoning mechanism that agents can use to generate and evaluate persuasive elements, such as promises of future rewards, to support the offers they make during negotiation. These persuasive elements aim to make offers more attractive over multiple encounters given the absence of information about an opponent's discount factors or exact payoffs. Specifically, we empirically demonstrate that agents are able to achieve a larger number of agreements and a higher expected utility over repeated encounters when they are given the capability to give or ask for rewards. Moreover, we develop a novel strategy using this protocol and show that it outperforms existing state of the art heuristic negotiation models. Finally, the applicability of persuasive negotiation and CREDIT is exemplified through a practical implementation in a pervasive computing environment. In this context, the negotiation mechanism is implemented in an instant messaging platform (JABBER) and used to resolve conflicts between group and individual preferences that arise in a meeting room scenario. In particular, we show how persuasive negotiation and trust permit a flexible management of interruptions by allowing intrusions to happen at appropriate times during the meeting while still managing to satisfy the preferences of all parties present.},
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In this thesis, we propose a panoply of tools and techniques to manage inter-agent dependencies in open, distributed multi-agent systems that have significant degrees of uncertainty. In particular, we focus on situations in which agents are involved in repeated interactions where they need to negotiate to resolve conflicts that may arise between them. To this end, we endow agents with decision making models that exploit the notion of trust and use persuasive techniques during the negotiation process to reduce the level of uncertainty and achieve better deals in the long run. Firstly, we develop and evaluate a new trust model (called CREDIT) that allows agents to measure the degree of trust they should place in their opponents. This model reduces the uncertainty that agents have about their opponents' reliability. Thus, over repeated interactions, CREDIT enables agents to model their opponents' reliability using probabilistic techniques and a fuzzy reasoning mechanism that allows the combination of measures based on reputation (indirect interactions) and confidence (direct interactions). In so doing, CREDIT takes a wider range of behaviour-influencing factors into account than existing models, including the norms of the agents and the institution within which transactions occur. We then explore a novel application of trust models by showing how the measures developed in CREDIT ca be applied negotiations in multiple encounters. Specifically we show that agents that use CREDIT are able to avoid unreliable agents, both during the selection of interaction partners and during the negotiation process itself by using trust to adjust their negotiation stance. Also, we empirically show that agents are able to reach good deals with agents that are unreliable to some degree (rather than completely unreliable) and with those that try to strategically exploit their opponent. Secondly, having applied CREDIT to negotiations, we further extend the application of trust to reduce uncertainty about the reliability of agents in mechanism design (where the honesty of agents is elicited by the protocol). Thus, we develop $backslash$acftbmd that allows agents using a trust model (such as CREDIT) to reach efficient agreements that choose the most reliable agents in the long run. In particular, we show that our mechanism enforces truth-telling from the agents (i.e. it is incentive compatible), both about their perceived reliability of their opponent and their valuations for the goods to be traded. In proving the latter properties, our trust-based mechanism is shown to be the first reputation mechanism that implements individual rationality, incentive compatibility, and efficiency. Our trust-based mechanism is also empirically evaluated and shown to be better than other comparable models in reaching the outcome that maximises all the negotiating agents' utilities and in choosing the most reliable agents in the long run. Thirdly, having explored ways to reduce uncertainties about reliability and honesty, we use persuasive negotiation techniques to tackle issues associated with uncertainties that agents have about the preferences and the space of possible agreements. To this end, we propose a novel protocol and reasoning mechanism that agents can use to generate and evaluate persuasive elements, such as promises of future rewards, to support the offers they make during negotiation. These persuasive elements aim to make offers more attractive over multiple encounters given the absence of information about an opponent's discount factors or exact payoffs. Specifically, we empirically demonstrate that agents are able to achieve a larger number of agreements and a higher expected utility over repeated encounters when they are given the capability to give or ask for rewards. Moreover, we develop a novel strategy using this protocol and show that it outperforms existing state of the art heuristic negotiation models. Finally, the applicability of persuasive negotiation and CREDIT is exemplified through a practical implementation in a pervasive computing environment. In this context, the negotiation mechanism is implemented in an instant messaging platform (JABBER) and used to resolve conflicts between group and individual preferences that arise in a meeting room scenario. In particular, we show how persuasive negotiation and trust permit a flexible management of interruptions by allowing intrusions to happen at appropriate times during the meeting while still managing to satisfy the preferences of all parties present.
196.
Ramchurn, Sarvapali; Sierra, C.; Godo, L.; Jennings, N. R.
Devising a trust model for multi-agent interactions using confidence and reputation Journal Article
In: International Journal of Applied Artificial Intelligence, vol. 18, no. 9-10, pp. 833–852, 2004.
@article{eps260155,
title = {Devising a trust model for multi-agent interactions using confidence and reputation},
author = {Sarvapali Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
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year = {2004},
date = {2004-01-01},
journal = {International Journal of Applied Artificial Intelligence},
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197.
Rahwan, I.; Ramchurn, Sarvapali; Jennings, N. R.; McBurney, P.; Parsons, S.; Sonenberg, L.
Argumentation-based negotiation Journal Article
In: The Knowledge Engineering Review, vol. 18, no. 4, pp. 343–375, 2003.
@article{eps258850,
title = {Argumentation-based negotiation},
author = {I. Rahwan and Sarvapali Ramchurn and N. R. Jennings and P. McBurney and S. Parsons and L. Sonenberg},
url = {http://eprints.soton.ac.uk/258850/},
year = {2003},
date = {2003-01-01},
journal = {The Knowledge Engineering Review},
volume = {18},
number = {4},
pages = {343–375},
abstract = {Negotiation is essential in settings where autonomous agents have con- flicting interests and a desire to cooperate. For this reason, mechanisms in which agents exchange potential agreements according to various rules of interaction have become very popular in recent years as evident, for example, in the auction and mechanism design community. However, a growing body of research is now emerging which points out limitations in such mechanisms and advocates the idea that agents can increase the likelihood and quality of an agreement by exchanging arguments which in- fluence each others? states. This community further argues that argument exchange is sometimes essential when various assumptions about agent rationality cannot be satisfied. To this end, in this article, we identify the main research motivations and ambitions behind work in the field. We then provide a conceptual framework through which we outline the core elements and features required by agents engaged in argumentation-based negotiation, as well as the environment that hosts these agents. For each of these elements, we survey and evaluate existing proposed techniques in the literature and highlight the major challenges that need to be addressed if argument-based negotiation research is to reach its full potential.},
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Negotiation is essential in settings where autonomous agents have con- flicting interests and a desire to cooperate. For this reason, mechanisms in which agents exchange potential agreements according to various rules of interaction have become very popular in recent years as evident, for example, in the auction and mechanism design community. However, a growing body of research is now emerging which points out limitations in such mechanisms and advocates the idea that agents can increase the likelihood and quality of an agreement by exchanging arguments which in- fluence each others? states. This community further argues that argument exchange is sometimes essential when various assumptions about agent rationality cannot be satisfied. To this end, in this article, we identify the main research motivations and ambitions behind work in the field. We then provide a conceptual framework through which we outline the core elements and features required by agents engaged in argumentation-based negotiation, as well as the environment that hosts these agents. For each of these elements, we survey and evaluate existing proposed techniques in the literature and highlight the major challenges that need to be addressed if argument-based negotiation research is to reach its full potential.
198.
Ramchurn, S. D.; Jennings, N. R.; Sierra, C.
Persuasive negotiation for autonomous agents: A rhetorical approach Proceedings Article
In: IJCAI Workshop on Computational Models of Natural Argument, pp. 9–17, 2003.
@inproceedings{eps258541,
title = {Persuasive negotiation for autonomous agents: A rhetorical approach},
author = {S. D. Ramchurn and N. R. Jennings and C. Sierra},
url = {http://eprints.soton.ac.uk/258541/},
year = {2003},
date = {2003-01-01},
booktitle = {IJCAI Workshop on Computational Models of Natural Argument},
pages = {9–17},
abstract = {Persuasive negotiation occurs when autonomous agents exchange proposals that are backed up by rhetorical arguments (such as threats, rewards, or appeals). The role of such rhetorical arguments is to persuade the negotiation opponent to accept proposals more readily. To this end, this paper presents a rhetorical model of persuasion that defines the main types of rhetorical particles that are used and that provides a decision making model to enable an agent to determine what type of rhetorical argument to send in a given context and how to evaluate rhetorical arguments that are received. The model is empirically evaluated and we show that it is effective and efficient in reaching agreements.},
keywords = {},
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Persuasive negotiation occurs when autonomous agents exchange proposals that are backed up by rhetorical arguments (such as threats, rewards, or appeals). The role of such rhetorical arguments is to persuade the negotiation opponent to accept proposals more readily. To this end, this paper presents a rhetorical model of persuasion that defines the main types of rhetorical particles that are used and that provides a decision making model to enable an agent to determine what type of rhetorical argument to send in a given context and how to evaluate rhetorical arguments that are received. The model is empirically evaluated and we show that it is effective and efficient in reaching agreements.
199.
Ramchurn, Sarvapali; Sierra, C.; Godo, L.; Jennings, N. R.
A computational trust model for multi-agent interactions based on confidence and reputation Proceedings Article
In: 6th International Workshop of Deception, Fraud and Trust in Agent Societies, pp. 69–75, 2003, (Event Dates: 2003).
@inproceedings{eps258542,
title = {A computational trust model for multi-agent interactions based on confidence and reputation},
author = {Sarvapali Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/258542/},
year = {2003},
date = {2003-01-01},
booktitle = {6th International Workshop of Deception, Fraud and Trust in Agent Societies},
pages = {69–75},
abstract = {In open environments in which autonomous agents can break contracts, computational models of trust have an important role to play in determining who to interact with and how interactions unfold. To this end, we develop such a trust model, based on confi- dence and reputation, and show how it can be concretely applied, using fuzzy sets, to guide agents in evaluating past interactions and in establishing new contracts with one another.},
note = {Event Dates: 2003},
keywords = {},
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In open environments in which autonomous agents can break contracts, computational models of trust have an important role to play in determining who to interact with and how interactions unfold. To this end, we develop such a trust model, based on confi- dence and reputation, and show how it can be concretely applied, using fuzzy sets, to guide agents in evaluating past interactions and in establishing new contracts with one another.
200.
Panzarasa, P.; Ramchurn, S. D.; Jennings, Nick
Intrusiveness, Trust and Argumentation: Using Automated Negotiation to Inhibit the Transmission of Disruptive Information Proceedings Article
In: Proceedings of the International Conference on Computational Social and Organizational Systems, 2002.
@inproceedings{eps272014,
title = {Intrusiveness, Trust and Argumentation: Using Automated Negotiation to Inhibit the Transmission of Disruptive Information},
author = {P. Panzarasa and S. D. Ramchurn and Nick Jennings},
url = {http://eprints.soton.ac.uk/272014/},
year = {2002},
date = {2002-01-01},
booktitle = {Proceedings of the International Conference on Computational Social and Organizational Systems},
abstract = {The question of how to promote the growth and diffusion of information has been extensively addressed by a wide research community. A common assumption underpinning most studies is that the information to be transmitted is useful and of high quality. In this paper, we endorse a complementary perspective. We investigate how the growth and diffusion of high quality information can be managed and maximized by preventing, dampening and minimizing the diffusion of low quality, unwanted information. To this end, we focus on the conflict between pervasive computing environments and the joint activities undertaken in parallel local social contexts. When technologies for distributed activities (e.g. mobile technology) develop, both artifacts and services that enable people to participate in non-local contexts are likely to intrude on local situations. As a mechanism for minimizing the intrusion of the technology, we develop a computational model of argumentation-based negotiation among autonomous agents. A key component in the model is played by trust: what arguments are used and how they are evaluated depend on how trustworthy the agents judge one another. To gain an insight into the implications of the model, we conduct a number of virtual experiments. Results enable us to explore how intrusiveness is affected by trust, the negotiation network and the agents' abilities of conducting argumentation.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The question of how to promote the growth and diffusion of information has been extensively addressed by a wide research community. A common assumption underpinning most studies is that the information to be transmitted is useful and of high quality. In this paper, we endorse a complementary perspective. We investigate how the growth and diffusion of high quality information can be managed and maximized by preventing, dampening and minimizing the diffusion of low quality, unwanted information. To this end, we focus on the conflict between pervasive computing environments and the joint activities undertaken in parallel local social contexts. When technologies for distributed activities (e.g. mobile technology) develop, both artifacts and services that enable people to participate in non-local contexts are likely to intrude on local situations. As a mechanism for minimizing the intrusion of the technology, we develop a computational model of argumentation-based negotiation among autonomous agents. A key component in the model is played by trust: what arguments are used and how they are evaluated depend on how trustworthy the agents judge one another. To gain an insight into the implications of the model, we conduct a number of virtual experiments. Results enable us to explore how intrusiveness is affected by trust, the negotiation network and the agents' abilities of conducting argumentation.
Sorry, no publications matched your criteria.
181.
Espinoza, Fredrik; Roure, David De; Hamfors, Ola; Hinz, Lucas; Holmberg, Jesper; Jansson, Carl-Gustaf; Jennings, Nick; Luck, Mike; L"onnqvist, Peter; Ramchurn, Sarvapali; Sandin, Anna; Thompson, Mark; Bylund, Markus
Intrusiveness Management for Focused, Efficient, and Enjoyable Activities Book Section
In: The Disappearing Computer: Interaction Design, System Infrastructures and Applications for Smart Environments, pp. 143–160, Springer, 2007.
@incollection{eps265985,
title = {Intrusiveness Management for Focused, Efficient, and Enjoyable Activities},
author = {Fredrik Espinoza and David De Roure and Ola Hamfors and Lucas Hinz and Jesper Holmberg and Carl-Gustaf Jansson and Nick Jennings and Mike Luck and Peter L"onnqvist and Sarvapali Ramchurn and Anna Sandin and Mark Thompson and Markus Bylund},
url = {http://eprints.soton.ac.uk/265985/},
year = {2007},
date = {2007-01-01},
booktitle = {The Disappearing Computer: Interaction Design, System Infrastructures and Applications for Smart Environments},
pages = {143–160},
publisher = {Springer},
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182.
Rahwan, T.; Ramchurn, S. D.; Dang, V. D.; Jennings, N. R.
Near-optimal anytime coalition structure generation Proceedings Article
In: 20th International Joint Conference on Artificial Intelligence (IJCAI), pp. 2365–2371, 2007.
@inproceedings{eps263074,
title = {Near-optimal anytime coalition structure generation},
author = {T. Rahwan and S. D. Ramchurn and V. D. Dang and N. R. Jennings},
url = {http://eprints.soton.ac.uk/263074/},
year = {2007},
date = {2007-01-01},
booktitle = {20th International Joint Conference on Artificial Intelligence (IJCAI)},
pages = {2365–2371},
abstract = {Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best set of agents that should participate in a given team. To this end, in this paper, we present a novel, anytime algorithms designed for this purpose. Our algorithm can generate solutions that either have a tight bound from the optimal or are optimal (depending on the objective) and works by partitioning the space in terms of a small set of elements that represent structures which contain coalitions of particular sizes. It then performs an online heuristic search that prunes the space and only considers valid and non-redundant coalition structures. We empirically show that we are able to find solutions that are, in the worst case, 99% efficient in 0.0043% of the time to find the optimal value by the state of the art dynamic programming (DP) algorithm (for 20 agents), using 33% less memory.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best set of agents that should participate in a given team. To this end, in this paper, we present a novel, anytime algorithms designed for this purpose. Our algorithm can generate solutions that either have a tight bound from the optimal or are optimal (depending on the objective) and works by partitioning the space in terms of a small set of elements that represent structures which contain coalitions of particular sizes. It then performs an online heuristic search that prunes the space and only considers valid and non-redundant coalition structures. We empirically show that we are able to find solutions that are, in the worst case, 99% efficient in 0.0043% of the time to find the optimal value by the state of the art dynamic programming (DP) algorithm (for 20 agents), using 33% less memory.
183.
Rahwan, Talal; Ramchurn, Sarvapali D.; Dang, Viet D.; Giovannucci, Andrea; Jennings, N. R.
Anytime Optimal Coalition Structure Generation Proceedings Article
In: 22nd Conference on Artificial Intelligence (AAAI), pp. 1184–1190, 2007.
@inproceedings{eps263433,
title = {Anytime Optimal Coalition Structure Generation},
author = {Talal Rahwan and Sarvapali D. Ramchurn and Viet D. Dang and Andrea Giovannucci and N. R. Jennings},
url = {http://eprints.soton.ac.uk/263433/},
year = {2007},
date = {2007-01-01},
booktitle = {22nd Conference on Artificial Intelligence (AAAI)},
pages = {1184–1190},
abstract = {Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best groups of agents to select to achieve some goal. To this end, in this paper, we present a novel, optimal anytime algorithm for this coalition structure generation problem that is significantly faster than previous algorithms designed for this purpose. Specifically, our algorithm can generate solutions by partitioning the space of all potential coalitions into sub-spaces that contain coalition structures that are similar, according to some criterion, such that these sub-spaces can be pruned by identifying their bounds. Using this representation, the algorithm then searches through only valid and unique coalition structures and selects the best among them using a branch-and-bound technique. We empirically show that we are able to find solutions that are optimal in 0.082% of the time taken by the state of the art dynamic programming algorithm (for 27 agents) using much less memory (O(2^ n) instead of O(3^ n) for the set of n agents). Moreover, our algorithm is the first to be able to solve the coalition structure generation problem for numbers of agents bigger than 27 in reasonable time (less than 90 minutes for 27 agents as opposed to around 2 months for the best previous solution).},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best groups of agents to select to achieve some goal. To this end, in this paper, we present a novel, optimal anytime algorithm for this coalition structure generation problem that is significantly faster than previous algorithms designed for this purpose. Specifically, our algorithm can generate solutions by partitioning the space of all potential coalitions into sub-spaces that contain coalition structures that are similar, according to some criterion, such that these sub-spaces can be pruned by identifying their bounds. Using this representation, the algorithm then searches through only valid and unique coalition structures and selects the best among them using a branch-and-bound technique. We empirically show that we are able to find solutions that are optimal in 0.082% of the time taken by the state of the art dynamic programming algorithm (for 27 agents) using much less memory (O(2^ n) instead of O(3^ n) for the set of n agents). Moreover, our algorithm is the first to be able to solve the coalition structure generation problem for numbers of agents bigger than 27 in reasonable time (less than 90 minutes for 27 agents as opposed to around 2 months for the best previous solution).
184.
Ramchurn, S. D.; Sierra, C.; Godo, L.; Jennings, N. R.
Negotiating using rewards. Journal Article
In: Artificial Intelligence Journal., vol. 171, no. 10-15, pp. 805–837, 2007.
@article{eps264225,
title = {Negotiating using rewards.},
author = {S. D. Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/264225/},
year = {2007},
date = {2007-01-01},
journal = {Artificial Intelligence Journal.},
volume = {171},
number = {10-15},
pages = {805–837},
abstract = {Negotiation is a fundamental interaction mechanism in multi-agent systems because it allows self-interested agents to come to mutually beneficial agreements and partition resources efficiently and effectively. Now, in many situations, the agents need to negotiate with one another many times and so developing strategies that are effective over repeated interactions is an important challenge. Against this background, a growing body of work has examined the use of Persuasive Negotiation (PN), which involves negotiating using rhetorical arguments (such as threats, rewards, or appeals), in trying to convince an opponent to accept a given offer. Such mechanisms are especially suited to repeated encounters because they allow agents to influence the outcomes of future negotiations, while negotiating a deal in the present one, with the aim of producing results that are beneficial to both parties. To this end, in this paper, we develop a comprehensive PN mechanism for repeated interactions that makes use of rewards that can be asked for or given to. Our mechanism consists of two parts. First, a novel protocol that structures the interaction by capturing the commitments that agents incur when using rewards. Second, a new reward generation algorithm that constructs promises of rewards in future interactions as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. We then go on to develop a specific negotiation tactic, based on this reward generation algorithm, and show that it can achieve significantly better outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation in a Multi-Move Prisoners? dilemma setting, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this.},
keywords = {},
pubstate = {published},
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}
Negotiation is a fundamental interaction mechanism in multi-agent systems because it allows self-interested agents to come to mutually beneficial agreements and partition resources efficiently and effectively. Now, in many situations, the agents need to negotiate with one another many times and so developing strategies that are effective over repeated interactions is an important challenge. Against this background, a growing body of work has examined the use of Persuasive Negotiation (PN), which involves negotiating using rhetorical arguments (such as threats, rewards, or appeals), in trying to convince an opponent to accept a given offer. Such mechanisms are especially suited to repeated encounters because they allow agents to influence the outcomes of future negotiations, while negotiating a deal in the present one, with the aim of producing results that are beneficial to both parties. To this end, in this paper, we develop a comprehensive PN mechanism for repeated interactions that makes use of rewards that can be asked for or given to. Our mechanism consists of two parts. First, a novel protocol that structures the interaction by capturing the commitments that agents incur when using rewards. Second, a new reward generation algorithm that constructs promises of rewards in future interactions as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. We then go on to develop a specific negotiation tactic, based on this reward generation algorithm, and show that it can achieve significantly better outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation in a Multi-Move Prisoners? dilemma setting, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this.
185.
Rogers, Alex; Dash, Rajdeep K.; Ramchurn, Sarvapali D.; Vytelingum, Perukrishnen; Jennings, N. R.
Coordinating Team Players within a Noisy Iterated Prisoner?s Dilemma Tournament Journal Article
In: Theoretical Computer Science, vol. 377, no. 1-3, pp. 243–259, 2007.
@article{eps263238,
title = {Coordinating Team Players within a Noisy Iterated Prisoner?s Dilemma Tournament},
author = {Alex Rogers and Rajdeep K. Dash and Sarvapali D. Ramchurn and Perukrishnen Vytelingum and N. R. Jennings},
url = {http://eprints.soton.ac.uk/263238/},
year = {2007},
date = {2007-01-01},
journal = {Theoretical Computer Science},
volume = {377},
number = {1-3},
pages = {243–259},
abstract = {In this paper, we present our investigation into the use of a team of players within a noisy Iterated Prisoner?s Dilemma (IPD) tournament. We show that the members of such a team are able to use a pre-arranged sequence of moves that they make at the start of each interaction in order to recognise one another, and that by coordinating their actions they can increase the chances that one of the team members wins the round-robin style tournament. We consider, in detail, the factors that influence the performance of this team and we show that the problem that the team members face, when they attempt to recognise one another within the noisy IPD tournament, is exactly analogous to the problem, studied in information theory, of communicating reliably over a noisy channel. Thus we demonstrate that we can use error correcting codes to implement this recognition, and by doing so, further optimise the performance of the team.},
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In this paper, we present our investigation into the use of a team of players within a noisy Iterated Prisoner?s Dilemma (IPD) tournament. We show that the members of such a team are able to use a pre-arranged sequence of moves that they make at the start of each interaction in order to recognise one another, and that by coordinating their actions they can increase the chances that one of the team members wins the round-robin style tournament. We consider, in detail, the factors that influence the performance of this team and we show that the problem that the team members face, when they attempt to recognise one another within the noisy IPD tournament, is exactly analogous to the problem, studied in information theory, of communicating reliably over a noisy channel. Thus we demonstrate that we can use error correcting codes to implement this recognition, and by doing so, further optimise the performance of the team.
186.
Rogers, Alex; Dash, Rajdeep K.; Ramchurn, Sarvapali D.; Vytelingum, Perukrishnen; Jennings, N. R.
Error-Correcting Codes for Team Coordination within a Noisy Iterated Prisoner?s Dilemma Tournament Book Section
In: Kendel, Graham; Yao, Xin; Chong, Siang Yew (Ed.): The Iterated Prisoners Dilemma Competition: Celebrating the 20th Anniversary, pp. 205–229, World Scientific, 2007.
@incollection{eps263264,
title = {Error-Correcting Codes for Team Coordination within a Noisy Iterated Prisoner?s Dilemma Tournament},
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editor = {Graham Kendel and Xin Yao and Siang Yew Chong},
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187.
Karunatillake, N. C.; Jennings, N. R.; Rahwan, I.; Ramchurn, S. D.
Managing Social Influences through Argumentation-Based Negotiation Proceedings Article
In: Third International Workshop on Argumentation in Multi-Agent Systems (ArgMAS 2006), pp. 35–52, 2006, (Event Dates: 8th May 2006).
@inproceedings{eps262022,
title = {Managing Social Influences through Argumentation-Based Negotiation},
author = {N. C. Karunatillake and N. R. Jennings and I. Rahwan and S. D. Ramchurn},
url = {http://eprints.soton.ac.uk/262022/},
year = {2006},
date = {2006-01-01},
booktitle = {Third International Workshop on Argumentation in Multi-Agent Systems (ArgMAS 2006)},
pages = {35–52},
abstract = {Social influences play an important part in the actions that an individual agent may perform within a multi-agent society. However, the incomplete knowledge and the diverse and conflicting influences present within such societies, may stop an agent from abiding by all its social influences. This may, in turn, lead to conflicts that the agents need to identify, manage, and resolve in order for the society to behave in a coherent manner. To this end, we present an empirical study of an argumentation-based negotiation (ABN) approach that allows the agents to detect such conflicts, and then manage and resolve them through the use of argumentative dialogues. To test our theory, we map our ABN model to a multi-agent task allocation scenario. Our results show that using an argumentation approach allows agents to both efficiently and effectively manage their social influences even under high degrees of incompleteness. Finally, we show that allowing agents to argue and resolve such conflicts early in the negotiation encounter increases their efficiency in managing social influences.},
note = {Event Dates: 8th May 2006},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Social influences play an important part in the actions that an individual agent may perform within a multi-agent society. However, the incomplete knowledge and the diverse and conflicting influences present within such societies, may stop an agent from abiding by all its social influences. This may, in turn, lead to conflicts that the agents need to identify, manage, and resolve in order for the society to behave in a coherent manner. To this end, we present an empirical study of an argumentation-based negotiation (ABN) approach that allows the agents to detect such conflicts, and then manage and resolve them through the use of argumentative dialogues. To test our theory, we map our ABN model to a multi-agent task allocation scenario. Our results show that using an argumentation approach allows agents to both efficiently and effectively manage their social influences even under high degrees of incompleteness. Finally, we show that allowing agents to argue and resolve such conflicts early in the negotiation encounter increases their efficiency in managing social influences.
188.
Ramchurn, S. D.; Sierra, C.; Godo, L.; Jennings, N. R.
Negotiating using rewards Proceedings Article
In: 5th Int. Conf. on Autonomous Agents and Multi-Agent Systems, pp. 400–407, 2006.
@inproceedings{eps262591,
title = {Negotiating using rewards},
author = {S. D. Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/262591/},
year = {2006},
date = {2006-01-01},
booktitle = {5th Int. Conf. on Autonomous Agents and Multi-Agent Systems},
journal = {Proc. 5th Int. Conf. on Autonomous Agents and Multi-Agent Systems, Hakodate, Japan},
pages = {400–407},
abstract = {In situations where self-interested agents interact repeatedly, it is important that they are endowed with negotiation techniques that enable them to reach agreements that are profitable in the long run. To this end, we devise a novel negotiation algorithm that generates promises of rewards in future interactions, as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. Moreover, we thus develop a specific negotiation tactic based on this reward generation algorithm and show that it can achieve significantly bettter outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this under concrete settings.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In situations where self-interested agents interact repeatedly, it is important that they are endowed with negotiation techniques that enable them to reach agreements that are profitable in the long run. To this end, we devise a novel negotiation algorithm that generates promises of rewards in future interactions, as a means of permitting agents to reach better agreements, in a shorter time, in the present encounter. Moreover, we thus develop a specific negotiation tactic based on this reward generation algorithm and show that it can achieve significantly bettter outcomes than existing benchmark tactics that do not use such inducements. Specifically, we show, via empirical evaluation, that our tactic can lead to a 26% improvement in the utility of deals that are made and that 21 times fewer messages need to be exchanged in order to achieve this under concrete settings.
189.
Ashri, R.; Ramchurn, S. D.; Sabater, J.; Luck, M.; Jennings, N. R.
Trust evaluation through relationship analysis Proceedings Article
In: 4th Int Joint Conf. on Autonomous Agents and Multi-Agent Systems, pp. 1005–1011, 2005.
@inproceedings{eps260806,
title = {Trust evaluation through relationship analysis},
author = {R. Ashri and S. D. Ramchurn and J. Sabater and M. Luck and N. R. Jennings},
url = {http://eprints.soton.ac.uk/260806/},
year = {2005},
date = {2005-01-01},
booktitle = {4th Int Joint Conf. on Autonomous Agents and Multi-Agent Systems},
journal = {Proceedings: 4th International Joint Conference on Autonomous Agents and Multi-Agent Systems},
pages = {1005–1011},
abstract = {Current mechanisms for evaluating the trustworthiness of an agent within an electronic marketplace depend either on using a history of interactions or on recommendations from other agents. In the first case, these requirements limit what an agent with no prior interaction history can do. In the second case, they transform the problem into one of trusting the recommending agent. However, these mechanisms do not consider the relationships between agents that arise through interactions (such as buying or selling) or through overarching organisational structures (such as hierarchical or flat), which can also aid in evaluating trustworthiness. In response, this paper outlines a method that enables agents to evaluate the trustworthiness of their counterparts, based solely on an analysis of such relationships. Specifically, relationships are identified using a generic technique in conjunction with a basic model for agentbased marketplaces. They are then interpreted through a trust model that enables the inference of trust valuations based on the different types of relationships. In this way, we provide a further component for a trust evaluation model that addresses some of the limitations of existing work.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Current mechanisms for evaluating the trustworthiness of an agent within an electronic marketplace depend either on using a history of interactions or on recommendations from other agents. In the first case, these requirements limit what an agent with no prior interaction history can do. In the second case, they transform the problem into one of trusting the recommending agent. However, these mechanisms do not consider the relationships between agents that arise through interactions (such as buying or selling) or through overarching organisational structures (such as hierarchical or flat), which can also aid in evaluating trustworthiness. In response, this paper outlines a method that enables agents to evaluate the trustworthiness of their counterparts, based solely on an analysis of such relationships. Specifically, relationships are identified using a generic technique in conjunction with a basic model for agentbased marketplaces. They are then interpreted through a trust model that enables the inference of trust valuations based on the different types of relationships. In this way, we provide a further component for a trust evaluation model that addresses some of the limitations of existing work.
190.
Blankenburg, B.; Dash, R. K.; Ramchurn, S. D.; Klusch, M.; Jennings, N. R.
Trusted kernel-based coalition formation Proceedings Article
In: Proc. 4th Int Joint Conf on Autonomous Agents and Multi-Agent Systems, pp. 989–996, 2005.
@inproceedings{eps260808,
title = {Trusted kernel-based coalition formation},
author = {B. Blankenburg and R. K. Dash and S. D. Ramchurn and M. Klusch and N. R. Jennings},
url = {http://eprints.soton.ac.uk/260808/},
year = {2005},
date = {2005-01-01},
booktitle = {Proc. 4th Int Joint Conf on Autonomous Agents and Multi-Agent Systems},
journal = {Proceedings: 4th International Joint Conference on Autonomous Agents and Multi-agent Systems},
pages = {989–996},
abstract = {We define Trusted Kernel-based Coalition Formation as a novel extension to the traditional kernel-based coalition formation process which ensures agents choose the most reliable coalition partners and are guaranteed to obtain the payment they deserve. To this end, we develop an encryption-based communication protocol and a payment scheme which ensure that agents cannot manipulate the mechanism to their own benefit. Moreover, we integrate a generic trust model in the coalition formation process that permits the selection of the most reliable agents over repeated coalition games. We empirically evaluate our mechanism when iterated and show that, in the long run, it always chooses the coalition structure that has the maximum expected value and determines the payoffs that match their level of reliability.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We define Trusted Kernel-based Coalition Formation as a novel extension to the traditional kernel-based coalition formation process which ensures agents choose the most reliable coalition partners and are guaranteed to obtain the payment they deserve. To this end, we develop an encryption-based communication protocol and a payment scheme which ensure that agents cannot manipulate the mechanism to their own benefit. Moreover, we integrate a generic trust model in the coalition formation process that permits the selection of the most reliable agents over repeated coalition games. We empirically evaluate our mechanism when iterated and show that, in the long run, it always chooses the coalition structure that has the maximum expected value and determines the payoffs that match their level of reliability.
191.
Ramchurn, S. D.; Jennings, N. R.
Trust in agent-based software Book Section
In: Mansell, R.; Collins, B. S. (Ed.): Trust and Crime in Information Societies, pp. 165–204, Elgar Publishing, 2005.
@incollection{eps260823,
title = {Trust in agent-based software},
author = {S. D. Ramchurn and N. R. Jennings},
editor = {R. Mansell and B. S. Collins},
url = {http://eprints.soton.ac.uk/260823/},
year = {2005},
date = {2005-01-01},
booktitle = {Trust and Crime in Information Societies},
pages = {165–204},
publisher = {Elgar Publishing},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
192.
Dash, R. K.; Ramchurn, S. D.; Jennings, N. R.
Trust-Based Mechanism Design Proceedings Article
In: 3rd Int. Conf. on Autonomous Agents and Multi-Agent Systems, pp. 748–755, 2004, (Event Dates: 19-23 July 2004).
@inproceedings{eps259352,
title = {Trust-Based Mechanism Design},
author = {R. K. Dash and S. D. Ramchurn and N. R. Jennings},
url = {http://eprints.soton.ac.uk/259352/},
year = {2004},
date = {2004-01-01},
booktitle = {3rd Int. Conf. on Autonomous Agents and Multi-Agent Systems},
pages = {748–755},
abstract = {We define trust-based mechanism design as an augmentation of traditional mechanism design in which agents take into account the degree of trust that they have in their counterparts when determining their allocations. To this end, we develop an efficient, individually rational, and incentive compatible mechanism based on trust. This mechanism is embedded in a task allocation scenario in which the trust in an agent is derived from the reported performance success of that agent by all the other agents in the system. We also empirically study the evolution of our mechanism when iterated and show that, in the long run, it always chooses the most successful and cheapest agents to fulfill an allocation and chooses better allocations than other comparable models when faced with biased reporting.},
note = {Event Dates: 19-23 July 2004},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We define trust-based mechanism design as an augmentation of traditional mechanism design in which agents take into account the degree of trust that they have in their counterparts when determining their allocations. To this end, we develop an efficient, individually rational, and incentive compatible mechanism based on trust. This mechanism is embedded in a task allocation scenario in which the trust in an agent is derived from the reported performance success of that agent by all the other agents in the system. We also empirically study the evolution of our mechanism when iterated and show that, in the long run, it always chooses the most successful and cheapest agents to fulfill an allocation and chooses better allocations than other comparable models when faced with biased reporting.
193.
Ramchurn, S. D.; Deitch, B.; Thompson, M. K.; Roure, D. C.; Jennings, N. R.; Luck, M.
Minimising intrusiveness in pervasive computing environments using multi-agent negotiation Proceedings Article
In: First Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous'04), pp. 364–372, IEEE, 2004, (Event Dates: August 22 - 26, 2004).
@inproceedings{eps259566,
title = {Minimising intrusiveness in pervasive computing environments using multi-agent negotiation},
author = {S. D. Ramchurn and B. Deitch and M. K. Thompson and D. C. Roure and N. R. Jennings and M. Luck},
url = {http://eprints.soton.ac.uk/259566/},
year = {2004},
date = {2004-01-01},
booktitle = {First Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous'04)},
pages = {364–372},
publisher = {IEEE},
abstract = {This paper highlights intrusiveness as a key issue in the field of pervasive computing environments and presents a multi-agent approach to tackling it. Specifically, we discuss how interruptions can impact on individual and group tasks and how they can be managed by taking into account user and group preferences through negotiation between software agents. The system we develop is implemented on the Jabber platform and is deployed in the context of a meeting room scenario.},
note = {Event Dates: August 22 - 26, 2004},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper highlights intrusiveness as a key issue in the field of pervasive computing environments and presents a multi-agent approach to tackling it. Specifically, we discuss how interruptions can impact on individual and group tasks and how they can be managed by taking into account user and group preferences through negotiation between software agents. The system we develop is implemented on the Jabber platform and is deployed in the context of a meeting room scenario.
194.
Ramchurn, S. D.; Huynh, T. D.; Jennings, N. R.
Trust in Multiagent Systems Journal Article
In: The Knowledge Engineering Review, vol. 19, no. 1, pp. 1–25, 2004.
@article{eps259564,
title = {Trust in Multiagent Systems},
author = {S. D. Ramchurn and T. D. Huynh and N. R. Jennings},
url = {http://eprints.soton.ac.uk/259564/},
year = {2004},
date = {2004-01-01},
journal = {The Knowledge Engineering Review},
volume = {19},
number = {1},
pages = {1–25},
abstract = {Trust is a fundamental concern in large-scale open distributed systems. It lies at the core of all interactions between the entities that have to operate in such uncertain and constantly changing environments. Given this complexity, these components, and the ensuing system, are increasingly being conceptualised, designed, and built using agent-based techniques and, to this end, this paper examines the specific role of trust in multi-agent systems. In particular, we survey the state of the art and provide an account of the main directions along which research efforts are being focused. In so doing, we critically evaluate the relative strengths and weaknesses of the main models that have been proposed and show how, fundamentally, they all seek to minimise the uncertainty in interactions. Finally, we outline the areas that require further research in order to develop a comprehensive treatment of trust in complex computational settings.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Trust is a fundamental concern in large-scale open distributed systems. It lies at the core of all interactions between the entities that have to operate in such uncertain and constantly changing environments. Given this complexity, these components, and the ensuing system, are increasingly being conceptualised, designed, and built using agent-based techniques and, to this end, this paper examines the specific role of trust in multi-agent systems. In particular, we survey the state of the art and provide an account of the main directions along which research efforts are being focused. In so doing, we critically evaluate the relative strengths and weaknesses of the main models that have been proposed and show how, fundamentally, they all seek to minimise the uncertainty in interactions. Finally, we outline the areas that require further research in order to develop a comprehensive treatment of trust in complex computational settings.
195.
Ramchurn, Sarvapali
Multi-Agent Negotiation using Trust and Persuasion PhD Thesis
University of Southampton, 2004.
@phdthesis{eps260200,
title = {Multi-Agent Negotiation using Trust and Persuasion},
author = {Sarvapali Ramchurn},
url = {http://eprints.soton.ac.uk/260200/},
year = {2004},
date = {2004-01-01},
school = {University of Southampton},
abstract = {In this thesis, we propose a panoply of tools and techniques to manage inter-agent dependencies in open, distributed multi-agent systems that have significant degrees of uncertainty. In particular, we focus on situations in which agents are involved in repeated interactions where they need to negotiate to resolve conflicts that may arise between them. To this end, we endow agents with decision making models that exploit the notion of trust and use persuasive techniques during the negotiation process to reduce the level of uncertainty and achieve better deals in the long run. Firstly, we develop and evaluate a new trust model (called CREDIT) that allows agents to measure the degree of trust they should place in their opponents. This model reduces the uncertainty that agents have about their opponents' reliability. Thus, over repeated interactions, CREDIT enables agents to model their opponents' reliability using probabilistic techniques and a fuzzy reasoning mechanism that allows the combination of measures based on reputation (indirect interactions) and confidence (direct interactions). In so doing, CREDIT takes a wider range of behaviour-influencing factors into account than existing models, including the norms of the agents and the institution within which transactions occur. We then explore a novel application of trust models by showing how the measures developed in CREDIT ca be applied negotiations in multiple encounters. Specifically we show that agents that use CREDIT are able to avoid unreliable agents, both during the selection of interaction partners and during the negotiation process itself by using trust to adjust their negotiation stance. Also, we empirically show that agents are able to reach good deals with agents that are unreliable to some degree (rather than completely unreliable) and with those that try to strategically exploit their opponent. Secondly, having applied CREDIT to negotiations, we further extend the application of trust to reduce uncertainty about the reliability of agents in mechanism design (where the honesty of agents is elicited by the protocol). Thus, we develop $backslash$acftbmd that allows agents using a trust model (such as CREDIT) to reach efficient agreements that choose the most reliable agents in the long run. In particular, we show that our mechanism enforces truth-telling from the agents (i.e. it is incentive compatible), both about their perceived reliability of their opponent and their valuations for the goods to be traded. In proving the latter properties, our trust-based mechanism is shown to be the first reputation mechanism that implements individual rationality, incentive compatibility, and efficiency. Our trust-based mechanism is also empirically evaluated and shown to be better than other comparable models in reaching the outcome that maximises all the negotiating agents' utilities and in choosing the most reliable agents in the long run. Thirdly, having explored ways to reduce uncertainties about reliability and honesty, we use persuasive negotiation techniques to tackle issues associated with uncertainties that agents have about the preferences and the space of possible agreements. To this end, we propose a novel protocol and reasoning mechanism that agents can use to generate and evaluate persuasive elements, such as promises of future rewards, to support the offers they make during negotiation. These persuasive elements aim to make offers more attractive over multiple encounters given the absence of information about an opponent's discount factors or exact payoffs. Specifically, we empirically demonstrate that agents are able to achieve a larger number of agreements and a higher expected utility over repeated encounters when they are given the capability to give or ask for rewards. Moreover, we develop a novel strategy using this protocol and show that it outperforms existing state of the art heuristic negotiation models. Finally, the applicability of persuasive negotiation and CREDIT is exemplified through a practical implementation in a pervasive computing environment. In this context, the negotiation mechanism is implemented in an instant messaging platform (JABBER) and used to resolve conflicts between group and individual preferences that arise in a meeting room scenario. In particular, we show how persuasive negotiation and trust permit a flexible management of interruptions by allowing intrusions to happen at appropriate times during the meeting while still managing to satisfy the preferences of all parties present.},
keywords = {},
pubstate = {published},
tppubtype = {phdthesis}
}
In this thesis, we propose a panoply of tools and techniques to manage inter-agent dependencies in open, distributed multi-agent systems that have significant degrees of uncertainty. In particular, we focus on situations in which agents are involved in repeated interactions where they need to negotiate to resolve conflicts that may arise between them. To this end, we endow agents with decision making models that exploit the notion of trust and use persuasive techniques during the negotiation process to reduce the level of uncertainty and achieve better deals in the long run. Firstly, we develop and evaluate a new trust model (called CREDIT) that allows agents to measure the degree of trust they should place in their opponents. This model reduces the uncertainty that agents have about their opponents' reliability. Thus, over repeated interactions, CREDIT enables agents to model their opponents' reliability using probabilistic techniques and a fuzzy reasoning mechanism that allows the combination of measures based on reputation (indirect interactions) and confidence (direct interactions). In so doing, CREDIT takes a wider range of behaviour-influencing factors into account than existing models, including the norms of the agents and the institution within which transactions occur. We then explore a novel application of trust models by showing how the measures developed in CREDIT ca be applied negotiations in multiple encounters. Specifically we show that agents that use CREDIT are able to avoid unreliable agents, both during the selection of interaction partners and during the negotiation process itself by using trust to adjust their negotiation stance. Also, we empirically show that agents are able to reach good deals with agents that are unreliable to some degree (rather than completely unreliable) and with those that try to strategically exploit their opponent. Secondly, having applied CREDIT to negotiations, we further extend the application of trust to reduce uncertainty about the reliability of agents in mechanism design (where the honesty of agents is elicited by the protocol). Thus, we develop $backslash$acftbmd that allows agents using a trust model (such as CREDIT) to reach efficient agreements that choose the most reliable agents in the long run. In particular, we show that our mechanism enforces truth-telling from the agents (i.e. it is incentive compatible), both about their perceived reliability of their opponent and their valuations for the goods to be traded. In proving the latter properties, our trust-based mechanism is shown to be the first reputation mechanism that implements individual rationality, incentive compatibility, and efficiency. Our trust-based mechanism is also empirically evaluated and shown to be better than other comparable models in reaching the outcome that maximises all the negotiating agents' utilities and in choosing the most reliable agents in the long run. Thirdly, having explored ways to reduce uncertainties about reliability and honesty, we use persuasive negotiation techniques to tackle issues associated with uncertainties that agents have about the preferences and the space of possible agreements. To this end, we propose a novel protocol and reasoning mechanism that agents can use to generate and evaluate persuasive elements, such as promises of future rewards, to support the offers they make during negotiation. These persuasive elements aim to make offers more attractive over multiple encounters given the absence of information about an opponent's discount factors or exact payoffs. Specifically, we empirically demonstrate that agents are able to achieve a larger number of agreements and a higher expected utility over repeated encounters when they are given the capability to give or ask for rewards. Moreover, we develop a novel strategy using this protocol and show that it outperforms existing state of the art heuristic negotiation models. Finally, the applicability of persuasive negotiation and CREDIT is exemplified through a practical implementation in a pervasive computing environment. In this context, the negotiation mechanism is implemented in an instant messaging platform (JABBER) and used to resolve conflicts between group and individual preferences that arise in a meeting room scenario. In particular, we show how persuasive negotiation and trust permit a flexible management of interruptions by allowing intrusions to happen at appropriate times during the meeting while still managing to satisfy the preferences of all parties present.
196.
Ramchurn, Sarvapali; Sierra, C.; Godo, L.; Jennings, N. R.
Devising a trust model for multi-agent interactions using confidence and reputation Journal Article
In: International Journal of Applied Artificial Intelligence, vol. 18, no. 9-10, pp. 833–852, 2004.
@article{eps260155,
title = {Devising a trust model for multi-agent interactions using confidence and reputation},
author = {Sarvapali Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/260155/},
year = {2004},
date = {2004-01-01},
journal = {International Journal of Applied Artificial Intelligence},
volume = {18},
number = {9-10},
pages = {833–852},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
197.
Rahwan, I.; Ramchurn, Sarvapali; Jennings, N. R.; McBurney, P.; Parsons, S.; Sonenberg, L.
Argumentation-based negotiation Journal Article
In: The Knowledge Engineering Review, vol. 18, no. 4, pp. 343–375, 2003.
@article{eps258850,
title = {Argumentation-based negotiation},
author = {I. Rahwan and Sarvapali Ramchurn and N. R. Jennings and P. McBurney and S. Parsons and L. Sonenberg},
url = {http://eprints.soton.ac.uk/258850/},
year = {2003},
date = {2003-01-01},
journal = {The Knowledge Engineering Review},
volume = {18},
number = {4},
pages = {343–375},
abstract = {Negotiation is essential in settings where autonomous agents have con- flicting interests and a desire to cooperate. For this reason, mechanisms in which agents exchange potential agreements according to various rules of interaction have become very popular in recent years as evident, for example, in the auction and mechanism design community. However, a growing body of research is now emerging which points out limitations in such mechanisms and advocates the idea that agents can increase the likelihood and quality of an agreement by exchanging arguments which in- fluence each others? states. This community further argues that argument exchange is sometimes essential when various assumptions about agent rationality cannot be satisfied. To this end, in this article, we identify the main research motivations and ambitions behind work in the field. We then provide a conceptual framework through which we outline the core elements and features required by agents engaged in argumentation-based negotiation, as well as the environment that hosts these agents. For each of these elements, we survey and evaluate existing proposed techniques in the literature and highlight the major challenges that need to be addressed if argument-based negotiation research is to reach its full potential.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Negotiation is essential in settings where autonomous agents have con- flicting interests and a desire to cooperate. For this reason, mechanisms in which agents exchange potential agreements according to various rules of interaction have become very popular in recent years as evident, for example, in the auction and mechanism design community. However, a growing body of research is now emerging which points out limitations in such mechanisms and advocates the idea that agents can increase the likelihood and quality of an agreement by exchanging arguments which in- fluence each others? states. This community further argues that argument exchange is sometimes essential when various assumptions about agent rationality cannot be satisfied. To this end, in this article, we identify the main research motivations and ambitions behind work in the field. We then provide a conceptual framework through which we outline the core elements and features required by agents engaged in argumentation-based negotiation, as well as the environment that hosts these agents. For each of these elements, we survey and evaluate existing proposed techniques in the literature and highlight the major challenges that need to be addressed if argument-based negotiation research is to reach its full potential.
198.
Ramchurn, S. D.; Jennings, N. R.; Sierra, C.
Persuasive negotiation for autonomous agents: A rhetorical approach Proceedings Article
In: IJCAI Workshop on Computational Models of Natural Argument, pp. 9–17, 2003.
@inproceedings{eps258541,
title = {Persuasive negotiation for autonomous agents: A rhetorical approach},
author = {S. D. Ramchurn and N. R. Jennings and C. Sierra},
url = {http://eprints.soton.ac.uk/258541/},
year = {2003},
date = {2003-01-01},
booktitle = {IJCAI Workshop on Computational Models of Natural Argument},
pages = {9–17},
abstract = {Persuasive negotiation occurs when autonomous agents exchange proposals that are backed up by rhetorical arguments (such as threats, rewards, or appeals). The role of such rhetorical arguments is to persuade the negotiation opponent to accept proposals more readily. To this end, this paper presents a rhetorical model of persuasion that defines the main types of rhetorical particles that are used and that provides a decision making model to enable an agent to determine what type of rhetorical argument to send in a given context and how to evaluate rhetorical arguments that are received. The model is empirically evaluated and we show that it is effective and efficient in reaching agreements.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Persuasive negotiation occurs when autonomous agents exchange proposals that are backed up by rhetorical arguments (such as threats, rewards, or appeals). The role of such rhetorical arguments is to persuade the negotiation opponent to accept proposals more readily. To this end, this paper presents a rhetorical model of persuasion that defines the main types of rhetorical particles that are used and that provides a decision making model to enable an agent to determine what type of rhetorical argument to send in a given context and how to evaluate rhetorical arguments that are received. The model is empirically evaluated and we show that it is effective and efficient in reaching agreements.
199.
Ramchurn, Sarvapali; Sierra, C.; Godo, L.; Jennings, N. R.
A computational trust model for multi-agent interactions based on confidence and reputation Proceedings Article
In: 6th International Workshop of Deception, Fraud and Trust in Agent Societies, pp. 69–75, 2003, (Event Dates: 2003).
@inproceedings{eps258542,
title = {A computational trust model for multi-agent interactions based on confidence and reputation},
author = {Sarvapali Ramchurn and C. Sierra and L. Godo and N. R. Jennings},
url = {http://eprints.soton.ac.uk/258542/},
year = {2003},
date = {2003-01-01},
booktitle = {6th International Workshop of Deception, Fraud and Trust in Agent Societies},
pages = {69–75},
abstract = {In open environments in which autonomous agents can break contracts, computational models of trust have an important role to play in determining who to interact with and how interactions unfold. To this end, we develop such a trust model, based on confi- dence and reputation, and show how it can be concretely applied, using fuzzy sets, to guide agents in evaluating past interactions and in establishing new contracts with one another.},
note = {Event Dates: 2003},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In open environments in which autonomous agents can break contracts, computational models of trust have an important role to play in determining who to interact with and how interactions unfold. To this end, we develop such a trust model, based on confi- dence and reputation, and show how it can be concretely applied, using fuzzy sets, to guide agents in evaluating past interactions and in establishing new contracts with one another.
200.
Panzarasa, P.; Ramchurn, S. D.; Jennings, Nick
Intrusiveness, Trust and Argumentation: Using Automated Negotiation to Inhibit the Transmission of Disruptive Information Proceedings Article
In: Proceedings of the International Conference on Computational Social and Organizational Systems, 2002.
@inproceedings{eps272014,
title = {Intrusiveness, Trust and Argumentation: Using Automated Negotiation to Inhibit the Transmission of Disruptive Information},
author = {P. Panzarasa and S. D. Ramchurn and Nick Jennings},
url = {http://eprints.soton.ac.uk/272014/},
year = {2002},
date = {2002-01-01},
booktitle = {Proceedings of the International Conference on Computational Social and Organizational Systems},
abstract = {The question of how to promote the growth and diffusion of information has been extensively addressed by a wide research community. A common assumption underpinning most studies is that the information to be transmitted is useful and of high quality. In this paper, we endorse a complementary perspective. We investigate how the growth and diffusion of high quality information can be managed and maximized by preventing, dampening and minimizing the diffusion of low quality, unwanted information. To this end, we focus on the conflict between pervasive computing environments and the joint activities undertaken in parallel local social contexts. When technologies for distributed activities (e.g. mobile technology) develop, both artifacts and services that enable people to participate in non-local contexts are likely to intrude on local situations. As a mechanism for minimizing the intrusion of the technology, we develop a computational model of argumentation-based negotiation among autonomous agents. A key component in the model is played by trust: what arguments are used and how they are evaluated depend on how trustworthy the agents judge one another. To gain an insight into the implications of the model, we conduct a number of virtual experiments. Results enable us to explore how intrusiveness is affected by trust, the negotiation network and the agents' abilities of conducting argumentation.},
keywords = {},
pubstate = {published},
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The question of how to promote the growth and diffusion of information has been extensively addressed by a wide research community. A common assumption underpinning most studies is that the information to be transmitted is useful and of high quality. In this paper, we endorse a complementary perspective. We investigate how the growth and diffusion of high quality information can be managed and maximized by preventing, dampening and minimizing the diffusion of low quality, unwanted information. To this end, we focus on the conflict between pervasive computing environments and the joint activities undertaken in parallel local social contexts. When technologies for distributed activities (e.g. mobile technology) develop, both artifacts and services that enable people to participate in non-local contexts are likely to intrude on local situations. As a mechanism for minimizing the intrusion of the technology, we develop a computational model of argumentation-based negotiation among autonomous agents. A key component in the model is played by trust: what arguments are used and how they are evaluated depend on how trustworthy the agents judge one another. To gain an insight into the implications of the model, we conduct a number of virtual experiments. Results enable us to explore how intrusiveness is affected by trust, the negotiation network and the agents' abilities of conducting argumentation.
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}
}
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