Computational models of uncertainty reasoning in expert systems

AbstractThe use of support pairs associated with the facts and rules of a knowledge base of an expert system to capture various aspects of inductive reasoning is discussed. The concept of semantic unification is introduced with reference to fuzzy sets theory. In this respect a probabilistic interpretation for this semantic unification is described using a population voting model. Examples are discussed including default reasoning using support logic