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This paper addresses the role of abstraction in case-based reasoning. We develop a general framework for reusing cases at several levels of abstraction, which is particularly suited for describing and analyzing existing and designing new approaches of this kind. We show that in synthetic tasks (e.g. configuration, design, and planning), abstraction can be successfully used to improve the efficiency of similarity assessment, retrieval, and adaptation. Furthermore, a case-based planning system, called Paris, is described and analyzed in detail using this framework. An empirical study done with Paris demonstrates significant advantages concerning retrieval and adaptation efficiency as well as flexibility of adaptation. Finally, we show how other approaches from the literature can be classified according to the developed framework.
We present an approach to systematically describing case-based reasoning systems bydifferent kinds of criteria. One main requirement was the practical relevance of these criteria and their usability for real-life applications. We report on the results we achieved from a case study carried out in the INRECA1 Esprit project.
In dieser Arbeit wird ein fallbasiertes System entwickelt, das Angaben über existiertende fallbasierte Anwendungen und Werkzeuge verwaltet. Mit diesem System kann ein Entwickler von fallbasierten Systemen sich einen Überblick über den Stand der Technik verschaffen und vor allem Informationen über Systeme erhalten, die dem System, das er selbst entwickeln will, ähnlich sind.