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 like decision networks dispose of a sound fundamental 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 transformation and 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. An experimental example is given as demonstration of the described techniques.
展开▼
