The Issue of Knowledge Acquisition in the Design of Rule-based Expert Systems

Abstract

Knowledge acquisition is a crucial problem in the design of expert systems. In fact, bridging the gap between domain experts and expert system designers in constructing and mantaining a large rule base is a very demanding issue. In this paper we propose an approach to knowledge acquisition which is based on a deep restructuring of the usual architecture of an expert system. This includes: the partitioning of knowledge in a rule base and a strategy-rule base; the proposal of a flexible rule structure, the treatment of partial matching, the introduction of the new concept of goal in the inference process, and the design of a specific knowledge acquisition subsystem. The above issues are discussed in connection with a real application concerning safety in route transportation of hazardous materials.