An approach to legal reasoning based on a hybrid decision-support system

This paper describes argument structures to generate plausible explanations for the conclusions reached by rule-based reasoning (RBR), and provides a means of integrating with case-based reasoning (CBR). The area of applicati on is a legal domain, for which a hybrid RBR-CBR knowledge-based system was built. An underlying object-oriented knowledge representation scheme provi des a means of modelling both the structural relationships among knowledge entities (i.e. rules and cases) and the control structures among them. Lega l reports of previously-decided cases are used as a knowledge source for th e CBR part of the system. An argumentation facility is presented, for each predicted rule-based outcome, based on Toulmin's argument structures to pro vide support via justifications. The framework of similarity for the case b ase side is based on a model which exploits the fuzzy proximity relations. Retrieved cases are used to help the decision-maker in formulating the fina l outcome of a new case (whose similarity with the retrieved cases is deter mined from fuzzy proximity relations). The system is also capable of provid ing justification of the case selection process. (C) 1999 Elsevier Science Ltd. All rights reserved.