Retrieval, reuse, revision and retention in case-based reasoning

Ramon Lopez De Mantaras*, David Mcsherry, Derek Bridge, David Leake, Barry Smyth, Susan Craw, Boi Faltings, Mary Lou Maher, Michael T. Cox, Kenneth Forbus, Mark Keane, Agnar Aamodt, Ian Watsoni

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

416 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)215-240
Number of pages26
JournalKnowledge Engineering Review
Volume20
Issue number3
DOIs
StatePublished - Sep 2005

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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