Fuzzy prolog

Various methods of representing uncertainty are discussed including some fuzzy methods. Representation and calculation of fuzzy expressions are discussed and a symbolic representation of fuzzy quantities coupled with axiomatic evaluation is proposed. This is incorporated into the PROLOG language to produce a fuzzy version. Apart from enabling imprecise facts and rules to be expressed, a natural method of controlling the search is introduced, making the search tree admissible.Formal expression of heuristic information in the same language, FUZZY PROLOG, as the main problem language follows naturally and therefore allows the same executor to evaluate in both “problem” space and “heuristic” space.In addition, the use of variable functors in the specification of bidirectional logic is discussed. The paper shows two areas of application of higher order fuzzy predicates. As an introduction Warren's examples are outlined and used with variable functors to illustrate their use in describing some relatively conventional applications.Translation of English into horn clause format is described and is used to illustrate the simplicity of representation using variable functors. Alternative formulations are also explored, typically the use of the “meta-variable” in MICRO-PROLOG and using the “univ” operator.Representation of rule generation and inference is addressed. Examples are given where the expression of meta-rules in standard PROLOG are compared with the expression of the same rules using “variable” predicate symbols. Some meta-rules illustrated are clearly not universally valid and this leads to the addition of fuzzy tokens.