Chapter

Trust Management

Volume 3477 of the series Lecture Notes in Computer Science pp 193-209

A Probabilistic Trust Model for Handling Inaccurate Reputation Sources

  • Jigar PatelAffiliated withLancaster UniversityElectronics & Computer Science, University of Southampton
  • , W. T. Luke TeacyAffiliated withLancaster UniversityElectronics & Computer Science, University of Southampton
  • , Nicholas R. JenningsAffiliated withLancaster UniversityElectronics & Computer Science, University of Southampton
  • , Michael LuckAffiliated withLancaster UniversityElectronics & Computer Science, University of Southampton

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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 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.