Knowledge Based Systems And Fuzzy Boolean Programming

This paper discusses the applications of Fuzzy Boolean Programming (FBP) problems for representing and reasoning with Propositional Knowledge. The use of the models provided by the FBP are proposed to answer imprecise questions in precisely stated KBS. Also, the advantages of using Fuzzy Boolean Programming instead of classical ones are presented in the framework of Propositional Knowledge. Keywords. Approximate reasoning, fuzzy boolean programming, knowledge based systems. 1. Introduction In the last years, efficient methods performing automated reasoning have become increasingly important. Problems in automated reasoning in Artificial Intelligence (AI) are often represented in a language which is a derivation of the Predicate Calculus. By means of substituting constants and functions by variables (instantiation), statements in such a language are reduced to statements in the Propositional Calculus (Loveland, 1978; Nilsson, 1982). In Willians 1977 was shown that statements in the Pro..