An extension of a fuzzy reputation agent trust model (AFRAS) in the ART testbed

With the introduction of web services, users require an automated way of determining their reliability and even their matching to personal and subjective preferences. Therefore, trust modelling of web services, managed in an autonomous way by intelligent agents, is a challenging and relevant issue. Due to the dynamic and distributed nature of web services, recommendations of web services from third parties may also play an important role to build and update automated trust models. In this context, the agent reputation and trust (ART) testbed has been used to compare trust models in three international competitions. The testbed runs locally and defines an ART appraisal domain with a simulation engine, although the trust models may be applied to any kind of automated and remote services, such as web services. Our previous works proposed an already-published trust model called AFRAS that used fuzzy sets to represent reputation of service providers and of recommenders of such services. In this paper we describe the extension required in the trust model to participate in these competitions. The extension consists of a trust strategy that applies the AFRAS trust model to the ART testbed concepts and protocols. An implementation of this extension of AFRAS trust model has participated in the (Spanish and International) 2006 ART competitions. Using this ART platform and some of the agents who participated, we executed a set of ART games to evaluate the relevance of trust strategy over trust model, and the advantage of using fuzzy representation of trust and reputation.