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Open Access item Retrieval, reuse, revision and retention in case-based reasoning

Authors:Lopez de Mantaras, Ramon
McSherry, David
Bridge, Derek
Leake, David
Smyth, Barry
Craw, Susan
Faltings, Boi
Maher, Mary L.
Cox, Michael T.
Forbus, Kenneth
Keane, Mark
Aamodt, Agnar
Watson, Ian
Keywords:Artificial Intelligence, Case-Based Reasoning
Issue Date:2006
Publisher:Cambridge University Press
Citation:The Knowledge Engineering Review, 2006, 20 (3), 215-240.
Abstract:Case-based reasoning (CBR) is an approach to problem solving that emphasizes the role of prior experience during future problem solving (i.e., new problems are solved by reusing and if necessary adapting the solutions to similar problems that were solved in the past). It has enjoyed considerable success in a wide variety of problem solving tasks and domains. Following a brief overview of the traditional problem-solving cycle in CBR, we examine the cognitive science foundations of CBR and its relationship to analogical reasoning. We then review a representative selection of CBR research in the past few decades on aspects of retrieval, reuse, revision, and retention.
Description:El original está disponible en www.journals.cambridge.org
Appears in Collections:(IIIA) Artículos

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