A goal-dependent abstraction for legal reasoning by analogy

Artificial Intelligence and Law 5 (1-2):97-118 (1997)
This paper presents a new algorithm to find an appropriate similarityunder which we apply legal rules analogically. Since there may exist a lotof similarities between the premises of rule and a case in inquiry, we haveto select an appropriate similarity that is relevant to both thelegal rule and a top goal of our legal reasoning. For this purpose, a newcriterion to distinguish the appropriate similarities from the others isproposed and tested. The criterion is based on Goal-DependentAbstraction (GDA) to select a similarity such that an abstraction basedon the similarity never loses the necessary information to prove the ground (purpose of legislation) of the legal rule. In order to cope withour huge space of similarities, our GDA algorithm uses some constraintsto prune useless similarities.
Keywords legal reasoning  analogy  similarity  order-sorted logid  taxonomic hierarchy  goal-dependent abstraction
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DOI 10.1023/A:1008272013974
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