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ArtificialIntelligence and Law 1:113-208, 1992. 113 1992 Kluwer Academic Publishers. Printed in the Netherlands.
 

Summary: ArtificialIntelligence and Law 1:113-208, 1992. 113
1992 Kluwer Academic Publishers. Printed in the Netherlands.
Case-Based Reasoning and its Implications for Legal
Expert Systems
KEVIN D. ASHLEY
Assistant Professor ofLaw and Intelligent Systems,
University of Pittsburgh,
School of Law
and
Learning Research and Development Center,
Pittsburgh, PA 15260, U.S.A.
e-maih ashley@vms.cis.pitt.edu
tel: (412) 648-1495, 624-7496
(Received 16 November 1991, accepted 8 October 1992)
Abstract. Reasoners compare problems to prior cases to draw conclusions about a problem and guide decision
making. All Case-Based Reasoning (CBR) employs some methods for generalizing from cases to support
indexing and relevance assessment and evidences two basic inference methods: constraining search by tracing a
solution from a past case or evaluating a case by comparing it to past cases. Across domains and tasks, however,
humans reason with cases in subtly different ways evidencing different mixes of and mechanisms for these
components.

  

Source: Ashley, Kevin D. - Learning Research and Development Center, University of Pittsburgh

 

Collections: Computer Technologies and Information Sciences