Engineering Trust Alignment: a First Approach

Abstract. In open multi-agent systems trust models are an important tool for agents to achieve effective interactions. However, in these kinds of open systems, the agents do not necessarily use the same, or even similar, trust models, leading to semantic differences between trust eval-uations in the different agents. Hence, to successfully use communicated trust evaluations, the agents need to align their trust models. We ex-plicate that currently proposed solutions, such as common ontologies or ontology alignment methods, lead to additional problems and propose a novel approach. We show how the trust alignment can be formed by con-sidering the interactions agents share. We describe our implementation of a method, which uses inductive learning algorithms, to accomplish this alignment and test it in an example scenario.