Engendering Trust in Buying and Selling Agents by Discouraging the Reporting of Unfair Ratings

In this paper, we examine the application of electronic mar-ketplaces, populated by buying and selling agents represent-ing their human users, learning about potential business part-ners and making recommendations to their users. We pro-pose a novel incentive mechanism to address the unfair rating problem arising when modeling the trustworthiness of selling agents relies on propagation of ratings provided by buying agents. In our mechanism, buying agents model other buy-ers and select the most trustworthy ones as their neighbors from which they can ask advice about sellers. In order to build reputation, sellers will model the reputation of buyers based on the number of their neighborhoods and increase val-ues of products to satisfy reputable buyers. In consequence, our mechanism creates incentive for buyers to provide fair ratings of sellers. We also discuss how a marketplace de-signed in this way leads to better profit both for buyers and sellers and as such fosters trust between the agents and their human users