Paper Info
Title
A probabilistic trust model for handling inaccurate reputation sources
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 in particular. 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 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
10.1007/11429760_14
iTrust
Keywords
Field
DocType
probabilistic trust model,agent-based virtual organisations,personal experience,past experience,inaccurate reputation source,false account,good interaction,reputation model,interaction partner,past interaction,particular attention,reputation information
Computer science,Computer security,Knowledge management,Software agent,Model-based reasoning,Computational trust,Probabilistic logic,User interface,Open system (systems theory),Distributed computing,Reputation
Conference
Volume
ISSN
ISBN
3477
0302-9743
3-540-26042-0
Citations 
PageRank 
References 
57
3.40
6
Authors
4
Name
Order
Citations
PageRank
Jigar Patel148823.57
W.T. Luke Teacy258828.88
Nicholas R. Jennings3193481564.35
Michael Luck43440275.97