Modelling legal argument: reasoning with cases and hypotheticals
Modelling legal argument: reasoning with cases and hypotheticals
An artificial intelligence approach to legal reasoning
An artificial intelligence approach to legal reasoning
Are user-contributed reviews community property?: exploring the beliefs and practices of reviewers
Proceedings of the 5th Annual ACM Web Science Conference
Experiences surveying the crowd: reflections on methods, participation, and reliability
Proceedings of the 5th Annual ACM Web Science Conference
Saving, reusing, and remixing web video: using attitudes and practices to reveal social norms
Proceedings of the 22nd international conference on World Wide Web
| Hi-index | 0.00 |
In this paper we examine the use of hypotheticals as a heuristic device to assist a case-based reasoner test the strengths, weaknesses, and ramifications of an analysis or argument by exploring and augmenting the space of known cases and indirectly, the attendant spaces of doctrine and argument. Our program, HYPO, works in the task domain of the law, particularly, the area of trade secret protection for software. We describe how HYPO generates a constellation of legally-meaningful hypothetical fact situations ("hypos") which are "near" a given fact situation. This is done in two steps: analysis of the given situation and then generation of the hypos. We discuss the heuristics HYPO currently uses, which include: (1) make a case weaker or stronger; (2) generate an extreme case; (3) generate a near miss; (4) manipulate a near win; and (5) generate a case on a related "dimension".