Inference and learning in fuzzy bayesian networks

Abstract

This paper deals with the development of a theory on bayesian networks. It proposes a modified algorithm for solving knowledge querying and information updating, when dealing with continuous variables and with probabilistic and uncertain instantiations. Fuzzy sets are used to rewrite the information contained in a database in order to reduce the complexity of the automatic learning of a bayesian net from data.