Taking advantage of models for legal classification

Abstract

Legal reasoning is often couched in terms of legal classification. We examine how three models of classification-Classical, Probabilistic and Exemplar-are used to perform legal classification. We argue that all three models of classification are implicitly applied by existing AI methods. The CABARET ("CAse-BAsed REasoning Tool") system is suggested as an architecture that applies all three models. The relative difficulty of revising knowledge in rule form, in HYPO-style dimension form, and exemplar form is considered.