In this paper we are interested in the fact that relevance and trustworthiness of information acquired by an agent X from a source F, strictly depends and derives from the X's trust in F with respect the kind of information. In particular, we are interested in analyzing the relevance of F's category as indicator for its trustworthiness with respect to the specific informative goals of X. In this paper we analyze an interactive cognitive model for searching information in a world where each agent can be considered as belonging to a specific agent's category. We also consider some kind of variability within the canonical categorial behavior and their consequent influence on the trustworthiness of provided information. The introduced interactive cognitive model also allows evaluating the trustworthiness of a source both on the basis of its category and on the basis of the past direct experience with it, so selecting the more adequate source with respect to the informative goals to achieve. We present a computational approach based on fuzzy sets and some selected simulation scenarios together with the discussion of their more interesting results.
The Relevance of Categories for Trusting Information Sources
Association for Computing Machinery,, New York, NY , Stati Uniti d'America
ACM transactions on Internet technology (Online) 15 (2015).
info:cnr-pdr/source/autori:Rino Falcone, Alessandro Sapienza, Cristiano Castelfranchi/titolo:The Relevance of Categories for Trusting Information Sources/doi:/rivista:ACM transactions on Internet technology (Online)/anno:2015/pagina_da:/pagina_a:/interva