KNOWLEDGE-BASED SYSTEMS VERIFICATION - A MACHINE LEARNING-BASED APPROACH

This paper addresses the problem of verification of knowledge bases. I t presents a knowledge-based system (KBS) verification approach that c onsiders system specifications and, consequently, knowledge bases to b e partially described when development starts. This partial descriptio n is not necessarily perfect, and our work aims at using machine learn ing techniques to progressively acquire new knowledge and then improve the quality of expert system knowledge bases (KB) by coping with two major KB anomalies; incompleteness and incorrectness. The KBs consider ed in our approach are expressed in different formalisms.