The Positive Power of Prejudice: A Computational Model for MAS

In MAS studies on Trust building and dynamics the role of direct/personal experience and of recommendations and reputation is proportionally overrated; while the importance of inferential processes in deriving the evaluation of trustees’ trustworthiness is underestimated and not enough exploited. In this paper we focus on the importance of generalized knowledge: agents' categories. The cognitive advantage of generalized knowledge can be synthesized in this claim: "It allows us to know a lot about something/somebody we do not directly know". At a social level this means that I can know a lot of things on people that I never met; it is social "prejudice" with its good side and fundamental contribution to social exchange. In this study we experimentally inquire the role played by categories' reputation with respect to the reputation and opinion on single agents: when it is better to rely on the first ones and when are more reliable the second ones. Our claim is that: the larger the population and the ignorance about the trustworthiness of each individual (as it happens in an open world) the more precious the role of trust in categories. In particular, we want investigate how the parameters defining the specific environment (number of agents, their interactions, transfer of reputation, and so on) determine the use of categories' reputation. This powerful inferential device has to be strongly present in WEB societies.