A MODEL FOR DESIGNING RULE-BASED EXPERT SYSTEMS

Resumen

The aim of this research is to develop a model for designing rule-based expert systems that uses the forward chaining method of inference. The striking aspect of this model is that the inference engine is based on a simple representation of rules and facts in relational database tables. Rules are decomposed and represented in tables at two levels, which allow the developing of expert systems in any programming language that supports SQL. The explanation facility uses tables containing the explanations of the result of each rule. The model proposed in this paper is based on a simple approach to represent facts and rules in relational database tables. The advantage of this model lies in focusing the design of rule-based expert systems toward knowledge representation in a database, reducing effort and programming difficulties.