Automatic fuzzy decision network transformation
Alexander Holland, Madjid Fathi · 2006
Abstract: Among the various types of decision support systems, decision-theoretic models and rule-based systems have gained considerable attraction. Both approaches have advantages and disadvantages. Decision-theoretic models dispose of a sound mathematical basis and comfortable knowledge engineering tools. Rule-based systems provide an efficient execution architecture and represent knowledge in an explicit, intelligible way. In this paper, we consider fuzzy rule-based systems as a special type of condensed decision model. We outline a knowledge compilation scheme which allows one to transform a decision-theoretic model into a fuzzy rule base and, hence, to combine the advantages of both approaches. Key-Words: Bayesian networks, decision networks, transformation, fuzzy rule base, knowledge representation 1