David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Artificial Intelligence and Law 2 (2):83-111 (1993)
For any system that uses previous experience to solve problems in new situations, it is necessary to identify the features in the situation that should match features in the previous cases through some process ofsituation analysis. In this paper, we examine this problem in the legal domain, where lawyers know it asissue spotting. In particular, we present an implementation of issue spotting in CHASER, a legal reasoning system that works in the domain of tort law.This approach is a compromise between generality and efficiency, and is applicable to a range of problems and domains besides legal reasoning. In particular, it presents a principled way to use multiple cases for a single problem by exploiting the inherent structure present in many domains.
|Keywords||Issue spotting torts case-based reasoning knowledge representation|
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