Title
Coping with inaccurate reputation sources: experimental analysis of a probabilistic trust model
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 Agent-based 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.
Year
DOI
Venue
2005
10.1145/1082473.1082624
AAMAS
Keywords
Field
DocType
probabilistic trust model,agent-based virtual organisations,personal experience,past experience,inaccurate reputation source,false account,good interaction,reputation model,experimental analysis,key driver,interaction partner,past interaction,reputation information,trust,reputation
Computer science,Coping (psychology),Software agent,Knowledge management,Computational trust,Probabilistic logic,Open system (systems theory),Reputation
Conference
ISBN
Citations 
PageRank 
1-59593-093-0
114
7.01
References 
Authors
7
4
Search Limit
100114
Name
Order
Citations
PageRank
W.T. Luke Teacy158828.88
Jigar Patel248823.57
Nicholas R. Jennings3193481564.35
Michael Luck43440275.97