Stereotypical trust and bias in dynamic multi-agent systems

Chris Burnett, Timothy J Norman, Katia Sycara

Research output: Contribution to journalArticlepeer-review

47 Citations (Scopus)


Large-scale multi-agent systems have the potential to be highly dynamic. Trust and reputation are crucial concepts in these environments, as it may be necessary for agents to rely on their peers to perform as expected, and learn to avoid untrustworthy partners. However, aspects of highly dynamic systems introduce issues which make the formation of trust relationships difficult. For example, they may be short-lived, precluding agents from gaining the necessary experiences to make an accurate trust evaluation. This paper describes a new approach, inspired by theories of human organisational behaviour, whereby agents generalise their experiences with previously encountered partners as stereotypes, based on the observable features of those partners and their behaviours. Subsequently, these stereotypes are applied when evaluating new and unknown partners. Furthermore, these stereotypical opinions can be communicated within the society, resulting in the notion of stereotypical reputation. We show how this approach can complement existing state-of-the-art trust models, and enhance the confidence in the evaluations that can be made about trustees when direct and reputational information is lacking or limited. Furthermore, we show how a stereotyping approach can help agents detect unwanted biases in the reputational opinions they receive from others in the society.
Original languageEnglish
Article number26
Number of pages22
JournalACM Transactions on Intelligent Systems and Technology
Issue number2
Publication statusPublished - Mar 2013


  • Multi-agent systems
  • Trust


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