Using fuzzy logic and Q-learning for trust modeling in multi-agent systems

Abstract

Often in multi-agent systems, agents interact with other agents to fulfill their own goals. Trust is, therefore, considered essential to make such interactions effective. This work describes a trust model that augments fuzzy logic with Q-learning to help trust evaluating agents select beneficial trustees for interaction in uncertain, open, dynamic, and… (More)
DOI: 10.15439/2014F482

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