Coping with Inaccurate Reputation Sources: Experimental Analysis of a Probabilistic Trust Model
Coping with Inaccurate Reputation Sources: Experimental Analysis of a Probabilistic Trust Model
This research aims to develop a model of trust and reputation that will ensure good interactions amongst software agents in large scale open systems. The following are key drivers for our model: (1) agents may be self-interested and may provide false accounts of experiences with other agents if it is beneficial for them to do so; (2) agents will need to interact with other agents with which they have little or no past experience. Against this background, we have developed TRAVOS (Trust and Reputation model for Agentbased Virtual OrganisationS) which models an agent's trust in an interaction partner. Specifically, trust is calculated using probability theory taking account of past interactions between agents. When there is a lack of personal experience between agents, the model draws upon reputation information gathered from third parties. In this latter case, we pay particular attention to handling the possibility that reputation information may be inaccurate.
Trust, Reputation, Probabilistic Trust
997-1004
Teacy, W. T. L.
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Patel, J.
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Jennings, N. R.
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Luck, M.
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2005
Teacy, W. T. L.
5f962a10-9ab5-4b19-8016-cc72588bdc6a
Patel, J.
f2ad7e18-bba0-4432-9d92-203cb5d55ca7
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Luck, M.
da93d46d-96db-4ed6-b54a-bfa53b406af3
Teacy, W. T. L., Patel, J., Jennings, N. R. and Luck, M.
(2005)
Coping with Inaccurate Reputation Sources: Experimental Analysis of a Probabilistic Trust Model.
Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, Utrecht, the, Netherlands.
.
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Conference or Workshop Item
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Abstract
This research aims to develop a model of trust and reputation that will ensure good interactions amongst software agents in large scale open systems. The following are key drivers for our model: (1) agents may be self-interested and may provide false accounts of experiences with other agents if it is beneficial for them to do so; (2) agents will need to interact with other agents with which they have little or no past experience. Against this background, we have developed TRAVOS (Trust and Reputation model for Agentbased Virtual OrganisationS) which models an agent's trust in an interaction partner. Specifically, trust is calculated using probability theory taking account of past interactions between agents. When there is a lack of personal experience between agents, the model draws upon reputation information gathered from third parties. In this latter case, we pay particular attention to handling the possibility that reputation information may be inaccurate.
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Published date: 2005
Additional Information:
Event Dates: July
Venue - Dates:
Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, Utrecht, the, Netherlands, 2005-07-01
Keywords:
Trust, Reputation, Probabilistic Trust
Organisations:
Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 260768
URI: http://eprints.soton.ac.uk/id/eprint/260768
PURE UUID: f3b1b4b9-c3da-48ac-9423-44cfb1daa967
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Date deposited: 14 Apr 2005
Last modified: 14 Mar 2024 06:42
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Contributors
Author:
W. T. L. Teacy
Author:
J. Patel
Author:
N. R. Jennings
Author:
M. Luck
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