Author:
LOPEZ DE MANTARAS RAMON,MCSHERRY DAVID,BRIDGE DEREK,LEAKE DAVID,SMYTH BARRY,CRAW SUSAN,FALTINGS BOI,MAHER MARY LOU,COX MICHAEL T,FORBUS KENNETH,KEANE MARK,AAMODT AGNAR,WATSON IAN
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.
Publisher
Cambridge University Press (CUP)
Subject
Artificial Intelligence,Software
Cited by
334 articles.
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