Trust-Based Selection of Partners

The community of multi-agent systems has been studying ways to improve the selection of partner agents for joint action. One of such approaches consists in estimating the trustworthiness of potential partners in order to decrease the risk inherent to interacting with unknown agents. In this paper, we study the effect of using trust in the process of selecting partners in electronic business. We empirically evaluate and compare different trust-based selection methods, which either use trust in a preselection phase previous to the negotiation, in the negotiation process, or in both of these stages. We here briefly introduce a computational model of trust that uses a simple machine learning mechanism to dynamically derive the expected tendencies of behavior of potential candidate partner agents. The results obtained in our comparison study allow us to point to the best trust-based selecting methods to use in specific situations.