Building an expert system language interpreter with the rule network technique

Abstract

Expert systems are increasingly prevailing in the fields of industry, business, and defense affairs. Expert system languages are key to the development, and play a decisive role on the quality, of expert systems. Three major components are required in an expert system language: knowledge representation, control, and developing tools. Current major expert system languages have their individual pros and cons, in terms of each component. We are developing a new expert system language which combines the advantages of these languages. Knowledge are expressed in the form of facts and rules which consist of predicates, without requiring rules to be Horn clauses. Facts may include variables and patterns are matched by unification. Control of execution is characterized by the recognize-act cycle of forward-chaining to reason about and answer user questions. Rules can be added and deleted dynamically. Friendly debugging facilities are provided. An interpreter, using the rule network technique, for the new language has been constructed, and test results show that the language is effective.

Supported by National Science Council under grant NSC 81-0408-E-110-02.