DANIEL: Integrating Case-Based and Rule-Based Reasoning in Law

Book One

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 12

Student Abstracts

This paper introduces DANlEL, an architecture for the integration of case-based reasoning and rule-based reasoning for legal interpretation. Rather than interleaving the reasoners and assuming their complementarity, like in previous approaches, they are applied concurrently. Conflicting interpretations are handled explicitly, based on domain knowledge and on the notion of redundancy. The principal problems of legal interpretation are the lack of deep models for legal reasoning, the existence of inherently ill-defined predicates and the frequent use of open-textured concepts, as pointed out in (Rissland and Skalak 1991). A hybrid approach to representing the legal sources and the use of meta-knowledge seems to be appropriate to solve these problems. The scope of DANIEL is not limited to this particular domain, since the noted difficulties do not occur exclusively, but prototypically in the law.