A reduction-graph model of precedent in legal analysis

Artificial Intelligence 150 (1-2):59-95 (2003)
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Abstract

Legal analysis is a task underlying many forms of legal problem solving. In the Anglo-American legal system, legal analysis is based in part on legal precedents, previously decided cases. This paper describes a reduction-graph model of legal precedents that accounts for a key characteristic of legal precedents: a precedent's relevance to subsequent cases is determined by the theory under which the precedent is decided. This paper identifies the implementation requirements for legal analysis using the reduction-graph model of legal precedents and describes GREBE, a program that satisfies these requirements.

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