A reduction-graph model of precedent in legal analysis

被引：11

作者：

Branting, LK ^{[1
]}

机构：

[1] N Carolina State Univ, Raleigh, NC 27695 USA

来源：

ARTIFICIAL INTELLIGENCE | 2003年 / 150卷 / 1-2期

关键词：

legal reasoning; case-based reasoning; analogy; reduction graph;

D O I：

10.1016/S0004-3702(03)00102-4

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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. (C) 2003 Elsevier B.V. All rights reserved.

引用

页码：59 / 95

页数：37