The Knowledge Engineering Review

As this article doesn't contain an abstract, the image below is necessary to enable the article to be indexed by certain search engines. The resolution of the full-text PDF is much higher than that shown here.


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


RAMON  LOPEZ DE MANTARAS a1 , DAVID  MCSHERRY a2 , DEREK  BRIDGE a3 , DAVID  LEAKE a4 , BARRY  SMYTH a5 , SUSAN  CRAW a6 , BOI  FALTINGS a7 , MARY LOU  MAHER a8 , MICHAEL T  COX a9 , KENNETH  FORBUS a10 , MARK  KEANE a11 , AGNAR  AAMODT a12 and IAN  WATSON a13
a1 Artificial Intelligence Research Institute, CSIC, Campus UAB, 08193 Bellaterra, Spain; e-mail: mantaras@iiia.csic.es
a2 School of Computing and Information Engineering, University of Ulster, Coleraine BT52 1SA, Northern Ireland, UK; e-mail: dmg.mcsherry@ulster.ac.uk
a3 Department of Computer Science, University College Cork, Ireland; e-mail: d.bridge@cs.ucc.ie
a4 Computer Science Department, Indiana University, Lindley Hall 215, 150 S. Woodlawn Avenue, Bloomington, IN 47405, USA; e-mail: leake@cs.indiana.edu
a5 School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland; e-mail: Barry.Smyth@ucd.ie
a6 School of Computing, The Robert Gordon University, Aberdeen AB25 1HG, Scotland, UK; e-mail: S.Craw@comp.rgu.ac.uk
a7 AI-Lab, Swiss Federal Institute of Technology, CH-1015 Lausanne, Switzerland; e-mail: Boi.Faltings@epfl.ch
a8 School of Information Technologies, University of Sydney, Australia; e-mail: marym@it.usyd.edu.au
a9 BBN Technologies, Cambridge, MA 02138, USA; e-mail: mcox@bbn.com
a10 EECS Department, Northwestern University, Evanston, IL 60208, USA; e-mail: forbus@northwestern.edu
a11 School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland; e-mail: mark.keane@ucd.ie
a12 Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway; e-mail: agnar.aamodt@idi.ntnu.no
a13 Department of Computer Science, University of Auckland, Auckland, New Zealand; e-mail: ian@cs.auckland.ac.nz

Article author query
lopez de mantaras r   [Google Scholar] 
mcsherry d   [Google Scholar] 
bridge d   [Google Scholar] 
leake d   [Google Scholar] 
smyth b   [Google Scholar] 
craw s   [Google Scholar] 
faltings b   [Google Scholar] 
maher m   [Google Scholar] 
cox m   [Google Scholar] 
forbus k   [Google Scholar] 
keane m   [Google Scholar] 
aamodt a   [Google Scholar] 
watson i   [Google Scholar] 
 

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.

(Published Online May 8 2006)