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

摘要

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 application is a legal domain, for which a hybrid RBR–CBR knowledge-based system was built. An underlying object-oriented knowledge representation scheme provides a means of modelling both the structural relationships among knowledge entities (i.e. rules and cases) and the control structures among them. Legal reports of previously-decided cases are used as a knowledge source for the CBR part of the system. An argumentation facility is presented, for each predicted rule-based outcome, based on Toulmin's argument structures to provide support via justifications. The framework of similarity for the case base side is based on a model which exploits the fuzzy proximity relations. Retrieved cases are used to help the decision-maker in formulating the final outcome of a new case (whose similarity with the retrieved cases is determined from fuzzy proximity relations). The system is also capable of providing justification of the case selection process.