Detecting change in legal concepts
ICAIL '95 Proceedings of the 5th international conference on Artificial intelligence and law
Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project
Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project
Teaching case-based argumentation through a model and examples
Teaching case-based argumentation through a model and examples
An ontology in OWL for legal case-based reasoning
Artificial Intelligence and Law
| Hi-index | 0.00 |
In this paper we describe an approach to reasoning with cases which takes into account the view that case law evolves through a series of decisions. This is in contrast to approaches which take as a starting point a set of decided cases, with no account taken of the order in which they were decided. The model of legal reasoning we follow is based on Levi's account which shows how decided cases often need to be reinterpreted in the light of subsequent decisions, so that features of cases wax and wane in importance. Our aim is to reproduce the arguments that could have been used in a given case, rather than to apply a retrospective understanding of the law to them. A second novel feature is that we use a general purpose ontology to describe the cases, rather than one developed specifically to model the pertinent cases. The paper describes a prototype implementation, and uses an example to illustrate how our approach works. After this case by case description we make some remarks on the insights gained, and draw some conclusions.