University of Trondheim,
College of Arts and Science,
Department of Informatics,
N-7055 Dragvoll, Norway.
Phone: +47 73 591838;
fax: +47 73 591733;
IIIA - Institut d'Investigació en Intel.ligència Artificial,
CSIC - Spanish Scientific Research Council,
Campus Universitat Autonòma de Barcelona,
08193 Bellaterra, Catalonia, Spain.
Voice: +34 3 5809570;
Fax: +34 3 5809661;
Case-based reasoning is a recent approach to problem solving and learning that has got a lot of attention over the last few years. Originating in the US, the basic idea and underlying theories have spread to other continents, and we are now within a period of highly active research in case-based reasoning in Europe, as well. This paper gives an overview of the foundational issues related to case-based reasoning, describes some of the leading methodological approaches within the field, and exemplifies the current state through pointers to some systems. Initially, a general framework is defined, to which the subsequent descriptions and discussions will refer. The framework is influenced by recent methodologies for knowledge level descriptions of intelligent systems. The methods for case retrieval, reuse, solution testing, and learning are summarized, and their actual realization is discussed in the light of a few example systems that represent different CBR approaches. We also discuss the role of case-based methods as one type of reasoning and learning method within an integrated system architecture.