Trust and reputation in open multi-agent systems
Trust and reputation are central to effective interactions in open multi-agent systems (MAS) in which agents, that are owned by a variety of stakeholders, continuously enter and leave the system. This openness means existing trust and reputation models cannot readily be used since their performance suffers when there are various (unforseen) changes in the environment. To this end, this thesis develops and evaluates FIRE, a trust and reputation model that enables autonomous agents in open MAS to evaluate the trustworthiness of their peers and to select good partners for interactions. FIRE integrates four sources of trust information under the same framework in order to provide a comprehensive assessment of an agent’s likely performance in open systems. Specifically, FIRE incorporates interaction trust, role-based trust, witness reputation, and certified reputation, that models trust resulting from direct experiences, role-based relationships, witness reports, and third-party references, respectively, to provide trust metrics in most circumstances. A novel model of reporter credibility has also been integrated to enable FIRE to effectively deal with inaccurate reports (from witnesses and referees). Finally, adaptive techniques have been introduced, which make use of the information gained from monitoring the environment, to dynamically adjust a number of FIRE’s parameters according to the actual situation an agent finds itself in. In all cases, a systematic empirical analysis is undertaken to evaluate the effectiveness of FIRE in terms of the agent’s performance.