Inside case-based explanation
Case-Based Reasoning (CBR) is a rapidly growing eld in AI. It is a memory-driven approach to problem solving; completed solutions to problems are stored in an `episodic ' memory, retrieved and adaptively applied to solve new problems. \\Inside Case-based Reasoning " [4], the popular predecessor to this book, is a well written introductory text for the subject. This book is an attempt to expand the theory of CBR from a problem solving technique to a model of cognition. The main philosophical claim is that Case-Based Explanation (CBE) underlies understanding and learning (p21): \\To understand is to satisfy some basic desire to make sense of what one is processing, to learn from what has been processed and formulate new desires about what one wants to learn. Our question is how people do this and how machines might do this." The book has some of the practical, `hands-on ' nature of its predecessor. The fundamental theoretical ideas are centred on the essential components (i.e. case retrieval, explanation evaluation and adaptation) of a CBE system. The book