FIRE: An Integrated Trust and Reputation Model for Open Multi-Agent Systems
FIRE: An Integrated Trust and Reputation Model for Open Multi-Agent Systems
Trust and reputation are central to effective interactions in open multi-agent systems in which agents, that are owned by a variety of stakeholders, can enter and leave the system at any time. This openness means existing trust and reputation models cannot readily be used. To this end, we present FIRE, a trust and reputation model that integrates a number of information sources to produce a comprehensive assessment of an agent’s likely performance. Specifically, FIRE incorporates interaction trust, role-based trust, witness reputation, and certified reputation to provide a trust metric in virtually all circumstances. FIRE is empirically benchmarked and is shown to help agents effectively select appropriate interaction partners
18-22
Huynh, Trung Dong
ddea6cf3-5a82-4c99-8883-7c31cf22dd36
Jennings, Nicholas R.
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Shadbolt, Nigel
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
2004
Huynh, Trung Dong
ddea6cf3-5a82-4c99-8883-7c31cf22dd36
Jennings, Nicholas R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Shadbolt, Nigel
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
Huynh, Trung Dong, Jennings, Nicholas R. and Shadbolt, Nigel
(2004)
FIRE: An Integrated Trust and Reputation Model for Open Multi-Agent Systems.
16th European Conference on Artificial Intelligence, Valencia, Spain.
.
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Conference or Workshop Item
(Paper)
Abstract
Trust and reputation are central to effective interactions in open multi-agent systems in which agents, that are owned by a variety of stakeholders, can enter and leave the system at any time. This openness means existing trust and reputation models cannot readily be used. To this end, we present FIRE, a trust and reputation model that integrates a number of information sources to produce a comprehensive assessment of an agent’s likely performance. Specifically, FIRE incorporates interaction trust, role-based trust, witness reputation, and certified reputation to provide a trust metric in virtually all circumstances. FIRE is empirically benchmarked and is shown to help agents effectively select appropriate interaction partners
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Published date: 2004
Additional Information:
Event Dates: 2004
Venue - Dates:
16th European Conference on Artificial Intelligence, Valencia, Spain, 2004-01-01
Organisations:
Web & Internet Science, Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 259559
URI: http://eprints.soton.ac.uk/id/eprint/259559
PURE UUID: 62003bc3-e863-4591-8508-af1d5c02530a
Catalogue record
Date deposited: 06 Sep 2004
Last modified: 14 Mar 2024 06:26
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Contributors
Author:
Trung Dong Huynh
Author:
Nicholas R. Jennings
Author:
Nigel Shadbolt
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