Retrieval, reuse, revision and retention in case-based reasoning | The Knowledge Engineering Review | Cambridge Core (original) (raw)
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Published online by Cambridge University Press: 08 May 2006
RAMON LOPEZ DE MANTARAS
Affiliation:
Artificial Intelligence Research Institute, CSIC, Campus UAB, 08193 Bellaterra, Spain; e-mail: mantaras@iiia.csic.es
DAVID MCSHERRY
Affiliation:
School of Computing and Information Engineering, University of Ulster, Coleraine BT52 1SA, Northern Ireland, UK; e-mail: dmg.mcsherry@ulster.ac.uk
DEREK BRIDGE
Affiliation:
Department of Computer Science, University College Cork, Ireland; e-mail: d.bridge@cs.ucc.ie
DAVID LEAKE
Affiliation:
Computer Science Department, Indiana University, Lindley Hall 215, 150 S. Woodlawn Avenue, Bloomington, IN 47405, USA; e-mail: leake@cs.indiana.edu
BARRY SMYTH
Affiliation:
School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland; e-mail: Barry.Smyth@ucd.ie
SUSAN CRAW
Affiliation:
School of Computing, The Robert Gordon University, Aberdeen AB25 1HG, Scotland, UK; e-mail: S.Craw@comp.rgu.ac.uk
BOI FALTINGS
Affiliation:
AI-Lab, Swiss Federal Institute of Technology, CH-1015 Lausanne, Switzerland; e-mail: Boi.Faltings@epfl.ch
MARY LOU MAHER
Affiliation:
School of Information Technologies, University of Sydney, Australia; e-mail: marym@it.usyd.edu.au
KENNETH FORBUS
Affiliation:
EECS Department, Northwestern University, Evanston, IL 60208, USA; e-mail: forbus@northwestern.edu
MARK KEANE
Affiliation:
School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland; e-mail: mark.keane@ucd.ie
AGNAR AAMODT
Affiliation:
Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway; e-mail: agnar.aamodt@idi.ntnu.no
IAN WATSON
Affiliation:
Department of Computer Science, University of Auckland, Auckland, New Zealand; e-mail: ian@cs.auckland.ac.nz
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.
Information
Type
Research Article
Copyright
2006 Cambridge University Press
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