The Representation of an Evolving System of Legal Concepts: II. Prototypes and Deformations
Proceedings of the Seventh International Joint Conference on Artificial Intelligence. Nowledge Representation. Pages 246-252.
Abstract
One of the principal goals of the TAXMAN project is to develop a theory about the structure and dynamics of legal concepts . using corporate tax law as an experimental pr oblem domain. In this paper we describe the " prototypeplus - deformation" model of legal conceptual structure : a concept is represented here by a prototypical description plus a sequence of deformations of the prototype. where the deformations are selected from among the possible "mapptngs" of one concrete description into another. The paper focuses on the set of mappings. which is the most important component of the model because it makes manifest the basic coherence of the conceptual space. The syntax and semantics of the mapptngs are described . and thet r role in the process of legal argument is suggested. The formal model is then illustrated by examples drawn from Eisner v. Macomber . an early stock dividend case.
@inproceedings{ijcai1981p51,
title = {The Representation of an Evolving System of Legal Concepts: II. Prototypes and Deformations},
author = {McCarty, L. Thorne and Sridharan, N. S.},
booktitle = {Proceedings of the Seventh International Joint Conference on
Artificial Intelligence, {IJCAI-81}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Roger C. Schank},
pages = {246--252},
year = {1981},
month = {8},
note = {Nowledge Representation},
url = {https://ijcai.org/proceedings/1981/51},
}
TY - CPAPER TI - The Representation of an Evolving System of Legal Concepts: II. Prototypes and Deformations AU - McCarty, L. Thorne AU - Sridharan, N. S. T2 - Proceedings of the Seventh International Joint Conference on Artificial Intelligence, IJCAI-81 PB - International Joint Conferences on Artificial Intelligence PY - 1981 SP - 246 EP - 252 UR - https://ijcai.org/proceedings/1981/51 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: