Representing teleological structure in case-based legal reasoning: the missing link

ABSTRACT

We argue that robust case-based models of legal knowledge that represent the way in which practicing professionals use legal decisions must contain a deeper domain model that represents the purposes behind the rules articulated in the cases. We propose a model for representing the teleological components of legal decisions, and we suggest a method for utilizing this representation in a HYPO-like framework for case-based legal argument.

REFERENCES

• 1: A~ak'y, K. 1990. Modelling Legal Argument: Reasoning with Cases and Hypotheticals. Can~ridg~ MA:MIT Press.
• 2: Kevin D. Ashley , Vincent Aleven, Toward an intelligent tutoring system for teaching law students to argue with cases, Proceedings of the 3rd international conference on Artificial intelligence and law, p.42-52, May 1991, Oxford, England [doi>10.1145/112646.112651]
• 3: L. K. Branting, Representing and reusing explanations of legal precedents, Proceedings of the 2nd international conference on Artificial intelligence and law, p.103-110, May 1989, Vancouver, British Columbia, Canada [doi>10.1145/74014.74029]
• 4: L. Karl Branting, Reasoning with portions of precedents, Proceedings of the 3rd international conference on Artificial intelligence and law, p.145-154, May 1991, Oxford, England [doi>10.1145/112646.112664]
• 5: Casner, J. & Leach, B. 1984. Cases and Text on ProperOt. Boston, MA:Little Brown.
• 6: Dukeminier, J. & Kricr, $. 1988. Teacher~ Manual, Property (2d. ed.). Boston, MA:Little Brown.
• 7: Anne von der Lieth Gardner, An artificial intelligence approach to legal reasoning, MIT Press, Cambridge, MA, 1987
• 8: S. R. Goldman , M. C. Dyer , M. Flowers, Precedent-based legal reasoning and knowledge acquisition in contract law: A process model, Proceedings of the 1st international conference on Artificial intelligence and law, p.210-221, May 27-29, 1997, Boston, Massachusetts, United States [doi>10.1145/41735.41759]
• 9: Hafner C. 1981. An Information Retrieval System Based on a Computer Model of Legal Knowledge. Ann At~r, MI:~ Research Press.
• 10: C. D. Hafner, Conceptual organization of case law knowledge bases, Proceedings of the 1st international conference on Artificial intelligence and law, p.35-42, May 27-29, 1997, Boston, Massachusetts, United States [doi>10.1145/41735.41740]
• 11: Kennedy, D. 1991. A Semiotics of Legal Argume, nL Syracuse Law Review 42(1): 75-116.
• 12: Klare, K. 1992. Torts Supplemem (on file with the authors).
• 13: Latson, A. 1992. The Law of Worlonen's Compensation, New York: Matthew Bc~r.
• 14: Petex~n, M. & Wate~D. 1985. An Expert Systems Approach to Evaluating Product Liability Cases. In Computing Power and Legal Reasoning, ed. Walter, C., 629-59. St. Paul, MN:West.
• 15: E. L. Rissland , K. D. Ashley, A case-based system for trade secrets law, Proceedings of the 1st international conference on Artificial intelligence and law, p.60-66, May 27-29, 1997, Boston, Massachusetts, United States [doi>10.1145/41735.41743]
• 16: Edwina L. Rissland , David B. Skalak, CABARET: rule interpretation in a hybrid architecture, International Journal of Man-Machine Studies, v.34 n.6, p.839-887, June 1991 [doi>10.1016/0020-7373(91)90013-W]
• 17: Roger C. Schank , David B. Leake, Creativity and learning in a case-based explainer, Machine learning: paradigms and methods, Elsevier North-Holland, Inc., New York, NY, 1990
• 18: Simon, H. 1977. Artificial Intelligence Systems tl~ Understand. In Proceedings IJCAI-77, 1064. Mcnalo Park, CA:International Joint Conferences on Artificial Intelligence, Inc.
• 19: Skalak, D. & Rissland, E. 1993. Arguments and Cases: An Inevitable Intertwining. Artificial Intelligence and law: An International Journal 1 (1):3-44.
• 20: Smith, J. & Deedman, C. 1987. Tho Application of Expert Systems Technology to Case-Based Law. In Proceedings of the First International Conference of Artificial Intelligence and Law, 85. New York:Association for Computing Machinery Press.
• 21: Winograd, T. 1972. Understanding Natural Language. Cognitive Psychology 3:8-11.
• 22: George Vossos , John Zeleznikow , Tharam Dillon , Vivian Vossos, An example of integrating legal case based reasoning with object-oriented rule-based systems: IKBALS II, Proceedings of the 3rd international conference on Artificial intelligence and law, p.31-41, May 1991, Oxford, England [doi>10.1145/112646.112650]

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.1 Applications and Expert Systems
          Subjects: Law

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.4 Knowledge Representation Formalisms and Methods
          Subjects: Representations (procedural and rule-based)

General Terms:
Legal Aspects