Uncertainty Management for Fuzzy Decision Support Systems

A new approach for uncertainty management for fuzzy, rule based decision support systems is proposed: The domain e:z:pert 's knowledge is e:z:pressed by a set of rules that frequently refer to vague and uncertain propositions. Th.e certainty of propositions is represented using intervals {a. bj e:z:pressing that the proposition's probability is at least a and at most b. Methods and techniques for computing the overall certainty of fuzzy compound propositions that have been defined by using logical connectives 'and', 'or' and 'not' are introduced. Different inference schemas for applying fuzzy rules by U$ing modus ponens are discussed. Different algorithms for combining evidence that has been received from different rules for the same proposition a.re provided. Th.e relationship of the approach to other approaches is analyzed and its problems of lcnowledge acquisition and knowledge repre.,entation are discussed in some detail. The basic concepts of a rule-based progra.mming language called PICASSO, for which the approach is a theoretical foundation, are outlined.