Abstract
Agents in open multi-agent systems must deal with the difficult problem of selecting interaction partners in the face of uncertainty about their behaviour. This is especially problematic if they have to interact with an agent they have not interacted with before. In this case they can turn to their peers for information about this potential partner. However, in scenarios where agents may be evaluated according to many different criteria for many different purposes, their peers' evaluations may be mismatched with regards to their own expectations. In this paper we present a novel method, using an argumentation framework, that allows agents to discuss and adapt their trust model. This allows agents to provide, and receive, personalized trust evaluations, better suited to the agent in need, as is shown in a prototypical experiment.
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