Enhanced maintenance and explanation of expert systems through explicit models of their development

Abstract

Following principled techniques in developing expert systems could greatly enhance their understandability for both users and system developers. We argue that the limited explanatory capabilities and difficulties in evolution encountered in current systems stem from their failure to represent knowledge required to design the system. The paper proposes an approach to expert system construction which attempts to identify that tacit knowledge, provide means for capturing it in the knowledge bases of expert systems, and apply it towards more perspicuous machine-generated explanations and more consistent and maintainable system organization.