Sequential Decision Making with Untrustworthy Service Providers
Sequential Decision Making with Untrustworthy Service Providers
In this paper, we deal with the sequential decision making problem of agents operating in computational economies, where there is uncertainty regarding the trustworthiness of service providers populating the environment. Specifically, we propose a generic Bayesian trust model, and formulate the optimal Bayesian solution to the exploration-exploitation problem facing the agents when repeatedly interacting with others in such environments. We then present a computationally tractable Bayesian reinforcement learning algorithm to approximate that solution by taking into account the expected value of perfect information of an agent's actions. Our algorithm is shown to dramatically outperform all previous finalists of the international Agent Reputation and Trust (ART) competition, including the winner from both years the competition has been run.
Trust, Reputation, Multiagent Systems, Uncertainty, Reinforcement Learning
755-762
Teacy, W. T. L.
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Chalkiadakis, G.
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Rogers, A.
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Jennings, N. R.
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May 2008
Teacy, W. T. L.
5f962a10-9ab5-4b19-8016-cc72588bdc6a
Chalkiadakis, G.
660ef7d2-f977-43a7-97f2-c85cc3bcf0a4
Rogers, A.
f9130bc6-da32-474e-9fab-6c6cb8077fdc
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Teacy, W. T. L., Chalkiadakis, G., Rogers, A. and Jennings, N. R.
(2008)
Sequential Decision Making with Untrustworthy Service Providers.
Proceedings of the 7th International Conference on Autonomous Agents and Multiagent Systems, Estoril, Portugal.
12 - 16 May 2008.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
In this paper, we deal with the sequential decision making problem of agents operating in computational economies, where there is uncertainty regarding the trustworthiness of service providers populating the environment. Specifically, we propose a generic Bayesian trust model, and formulate the optimal Bayesian solution to the exploration-exploitation problem facing the agents when repeatedly interacting with others in such environments. We then present a computationally tractable Bayesian reinforcement learning algorithm to approximate that solution by taking into account the expected value of perfect information of an agent's actions. Our algorithm is shown to dramatically outperform all previous finalists of the international Agent Reputation and Trust (ART) competition, including the winner from both years the competition has been run.
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Published date: May 2008
Additional Information:
Event Dates: 12th-16th May, 2008
Venue - Dates:
Proceedings of the 7th International Conference on Autonomous Agents and Multiagent Systems, Estoril, Portugal, 2008-05-12 - 2008-05-16
Keywords:
Trust, Reputation, Multiagent Systems, Uncertainty, Reinforcement Learning
Organisations:
Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 265168
URI: http://eprints.soton.ac.uk/id/eprint/265168
PURE UUID: 4be053df-862b-46d4-8c86-528dbecd5662
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Date deposited: 08 Feb 2008 10:06
Last modified: 14 Mar 2024 08:03
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Contributors
Author:
W. T. L. Teacy
Author:
G. Chalkiadakis
Author:
A. Rogers
Author:
N. R. Jennings
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