Case-Based Reasoning and Expert Systems

Abstract

Case-based reasoning (CBR) and expert systems have a long tradition in artificial intelligence: CBR since the late 1970s and expert systems since the late 1960s. While expert systems are based on expertise and expert reasoning capabilities for a specific area of responsibility, CBR is an approach for problem solving and learning of humans and computers. Starting from different research activities, CBR and expert systems have become overlapping research fields. In this talk the relationships between CBR and expert systems are analyzed from different perspectives like problem solving, learning, competence development, and knowledge types. As human case-based reasoners are quite successful in integrating problem-solving and learning, combining different problem solving strategies, utilizing different kinds of knowledge, and becoming experts for specific areas of responsibility, computer based expert systems do not have the reputation to be successful at these tasks. Based on this, the potential of CBR succeeding as future expert systems is discussed.