BankXX: a program to generate argument through case-base research

ABSTRACT

In this paper we describe a system, called BankXX, which generates arguments by performing a heuristic best-first search of a highly interconnected network of legal knowledge. The legal knowledge includes cases represented from a variety of points of view—cases as collections of facts, cases as dimensionally-analyzed fact situations, cases as bundles of citations, and cases as prototypical factual scripts—as well as legal theories represented in terms of domain factors. BankXX performs its search for useful information using one of three evaluation functions encoded at different levels of abstraction: the domain level, an “argument-piece” level, and the overall argument level. Evaluation at the domain level uses easily accessible information about the nodes, such as their type; evaluation at the argument-piece level uses information about generally useful components of case-based argument, such as best cases and supporting legal theories; evaluation at the overall-argument level uses factors, called argument dimensions, which address the overall substance and quality of an argument, such as the centrality of its supporting cases or the success record of its best theory. BankXX is instantiated in the area of personal bankruptcy governed by Chapter 13 of the U.S. Bankruptcy Code, which permits a debtor to be discharged from debts through completion of a court-approved payment plan. In particular, our system addresses the requirement that such Chapter 13 plans be “proposed in good faith.”

REFERENCES

• 1: Sergio Jose Alvarado, Understanding Editorial Text: A Computer Model of Argument Comprehension, Kluwer Academic Publishers, Norwell, MA, 1990
• 2: Kevin D. Ashley, Modeling Legal Arguments: Reasoning with Cases and Hypotheticals, MIT Press, Cambridge, MA, 1991
• 3: K. D. Ashley , E. L. Rissland, Ashley,K. D.-But, see, accord: generating blue book citations in HYPO, Proceedings of the 1st international conference on Artificial intelligence and law, p.67-74, May 27-29, 1997, Boston, Massachusetts, United States [doi>10.1145/41735.41744]
• 4: Avron Barr , Edward A. Feigenbaum , Paul R. Cohen, Handbook of AI, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1986
• 5: Raj Krishna Bhatnagar , Laveen N. Kanal, Construction of preferred causal hypotheses for reasoning with uncertain knowledge, 1989
• 6: J. Bing, Designing text retrieval systems for conceptual searching, Proceedings of the 1st international conference on Artificial intelligence and law, p.43-51, May 27-29, 1997, Boston, Massachusetts, United States [doi>10.1145/41735.41741]
• 7: L. Karl Branting, Building explanations from rules and structured cases, International Journal of Man-Machine Studies, v.34 n.6, p.797-837, June 1991 [doi>10.1016/0020-7373(91)90012-V]
• 8: J. P. Dick, Conceptual retrieval and case law, Proceedings of the 1st international conference on Artificial intelligence and law, p.106-115, May 27-29, 1997, Boston, Massachusetts, United States [doi>10.1145/41735.41748]
• 9: Lee D. Erman , Frederick Hayes-Roth , Victor R. Lesser , D. Raj Reddy, The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty, ACM Computing Surveys (CSUR), v.12 n.2, p.213-253, June 1980 [doi>10.1145/356810.356816]
• 10: Fikes, R. E., Hart, P. & Nilsson, N. J. (1972). Learning and executing generalized robot plans. Artificial Intelligence, 3, 251-288.
• 11: T. F. Gordon, An abductive theory of legal issues, International Journal of Man-Machine Studies, v.35 n.1, p.95-118, July 1991 [doi>10.1016/S0020-7373(07)80009-5]
• 12: Haf, ner, C. D. (1987). An information Retrieval System Based on a Computer Model of Legal Knowledge. Ph.D, Thesis, University of Michigan. Republished by UMI Research Press, Ann Arbor, MI (1981).
• 13: 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]
• 14: Lehnert, W. (1981). Plot Units and Narrative Summarization. Cognitive Science, 5(4).
• 15: Levi, E. H. (1949). An Introduction to Legal Reasoning. Chicago: University of Chicago Press.
• 16: McCarty, L. T. & Sridharan, N. S. (1982). A Computational Theory of Legal Argument (LRP-TR-13). Laboratory for Computer Science Research, Rutgers University, New Brunswick, NJ.
• 17: N. J. Nilsson, Principles of artificial intelligence, Morgan Kaufmann Publishers Inc., San Francisco, CA, 1980
• 18: Perelman, C. & Olbrechts-Tyteca, L. (1969). The New Rhetoric: A Treatise on Argumentation. Notre Dame, Indiana: University of Notre Dame Press.
• 19: Prakken, H. (1993). Logical Tools for Modelling Legal Argument. Ph.D. Thesis, Vrije Universiteit te Amsterdam, Amsterdam, The Netherlands.
• 20: 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]
• 21: Rissland, E. L., Valcarce, E, M. & Ashley, K. D. (1984). Explaining and Arguing with Examples. AAAI.84, Proceedings of the National Conference on Artificial Intelligence. Austin, TX. American Association for Artificial Intelligence.
• 22: Rosch, E. & Mervis, C. B. (1975). Family Resemblances: Studies in the Internal Structure of Categories. Cognitive Psychology, 7,573-605.
• 23: Daniel E. Rose , Richard K. Belew, A connectionist and symbolic hybrid for improving legal research, International Journal of Man-Machine Studies, v.35 n.1, p.1-33, July 1991 [doi>10.1016/S0020-7373(07)80006-X]
• 24: Shepard's. (1992). Shepard's Federal Citations. Colorado Springs, CO: Shepard's/McGraw-Hill.
• 25: Skalak, D. B. & Rissland, E. L. (1992). Arguments and Cases: An Inevitable Intertwining. Artificial Intelligence and Law: An International Journal, 1, 3-48.
• 26: Stucky, B. K. (1986). Understanding Legal Argument. Counselor Project Technical Memorandum 13. Department of Computer Science, University of Massachusetts, Amherst, MA.
• 27: Sycara, K. P. (1989). Argumentation: Planning Other Agents' Plans. Proceedings, Eleventh International Joint Conference on Artificial Intelligence, 517-523. Detroit, Mi. International Joint Conferences on Artificial Intelligence.
• 28: Toulmin, S. (1958). The Uses of Argument. Cambridge, England: Cambridge University Press.
• 29: West. (1993). St. Paul, MN: West Publishing Co.

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.2.8 Problem Solving, Control Methods, and Search
          Subjects: Graph and tree search strategies; Heuristic methods

General Terms:
Algorithms, Legal Aspects