Case-Based Reasoning Technology: From Foundations To Applications (Lecture Notes In Computer Science / Lecture Notes In Artificial Intelligence)

Humanexpertsarenotsystemsofrules,theyarelibrariesofexperiences. Riesbeck and Schank (1989, p.15) Broadlyspeaking,case-basedreasoning(CBR)is concernedwith solvingnew problems by adapting solutions that worked for similar problems in the past. As with Arti cial Intelligence in general, case-based reasoning deals with two di erent aspects of intelligence: A r st motivation is to establish cog- tive models in order to understand human thinking and behavior. A second motivationis to buildsystemswhichhelpto solvereal-worldproblems.These twofacetscanbeconsideredastwosidesofthesamecoin.Traditionally,CBR researchinEuropehasconcentratedverymuchonthesecondaspect,though, of course, successful projects are not possible without a sound theory. The objective of this book is to summarize the results of recent years of research in CBR. A strong emphasis is put on projects performed and - plications developed in Germany. However, research has not been performed in isolation. Rather, a large number of cooperations between research sites throughout the world have been established which provided a fertile ground for the community. Hence, it is only natural that work from colleagues from France, Ireland, the Netherlands, and the United States has been included in this volume. This book is not intended to be a textbook giving a comprehensive overview of the eld. Rather, the objective is to consider in detail di - ent potential application areas, to work out the pros and cons of using CBR and to summarize the lessons learned from projects. For this, we assume that the reader already has at least a basic understanding of what case-based reasoning is all about.