An approach on merging agents' trust distributions in a Possibilitic Domain

Sina Honari, Brigitte Jaumard, Jamal Bentahar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we propose a novel approach on merging the trust distributions of an explorer agent in its advisors with the trust distributions of the advisor agents in a target agent. These two sets of merged distributions represent the trust of different, yet connected, agents in a multi-agent system. The deduced distribution measures an approximation of the explorer agent's trust in the target agent. The proposed approach can serve as a building block for estimating the trust distribution of an agent of interest in the multi-agent systems, who is accessible indirectly through a set of sequentially connected agents. A common issue of modelling trust is the presence of uncertainty, which arises in scenarios where there is either lack of adequate information or variability in an agent's level of trustworthiness. In order to represent uncertainty, possibility distributions are used to model trust of the agents.

Original languageBritish English
Title of host publicationAgents and Artificial Intelligence
Subtitle of host publication4th International Conference, ICAART 2012 Vilamoura, Portugal, February 6-8, 2012 Revised Selected Papers
PublisherSpringer Verlag
Pages283-299
Number of pages17
ISBN (Print)9783642369063
DOIs
StatePublished - 2013

Publication series

NameCommunications in Computer and Information Science
Volume358
ISSN (Print)1865-0929

Keywords

  • Multi-agent systems
  • Possibility theory
  • Trust
  • Uncertainty

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