Abstract
A representation methodology for knowledge allowing multiple interpretations is described. It is based on the following conception of legal knowledge and its open texture. Since indeterminate, legal knowledge must be adapted to fit the circumstances of the cases to which it is applied. Whether a certain adaptation is lawful or not is measured by metaknowledge. But as this too is indeterminate, its adaptation to the case must be measured by metametaknowledge, etc. This hierarchical model of law is quite well-established and may serve well as a basis for a legal knowledge system. To account for the indeterminacy of law such a system should support the construction of different arguments for and against various interpretations of legal sources. However, automatizing this reasoning fully is unsound since it would imply a restriction to arguments defending interpretations anticipated at programming time. Therefore, the system must be interactive and the user's knowledge be furnished in a principled way. Contrary to the widespread opinion that classical logic is inadequate for representing open-textured knowledge, the framework outlined herein is given a formalization in first order logic.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Allen, L. E. & Saxon S. S. 1991. More IA Needed in AI: Interpretation Assistance for Coping with the Problem of Multiple Structural Interpretations. In Proceedings ofThe Third International Conference on Artificial Intelligence and Law, 53–61, Oxford: Association of Computing Machinery.
Aristotle 1982.Nicomachean Ethics. transl. H. Rackham, Loeb Classical Library 73, Cambridge, Mass: Harvard University Press.
Ashley, K. D. 1990.Modeling Legal Argument. Cambridge, Mass: MIT Press.
Ashley, K. D. & Rissland, E. L. 1985. Toward Modelling Legal Argument. In Pre-Proceedings ofThe Second International Congress, on Logic, Informatics, and Law, 97–106. Florence.
Barklund, J. & Hamfelt, A. 1993. Formalising Multiple Interpretations of Law as Metalogic Programs,J. Law, Computer & Artificial Intelligence 2: 165–193.
Barklund, J. & Hamfelt, A. 1994. Hierarchical Representation of Legal Knowledge with Metaprogramming in Logic,J. Logic Programming 18: 55–80.
Bench-Capon, T.J.M. & Coenen, F.P. 1992. Isomorphism and Legal Knowledge Based Systems,J. Artificial Intelligence and Law 1: 65–86.
Bench-Capon, T. & Sergot, M. 1988. Toward a Rule Based Representation of Open Texture in Law. In C. Walter (ed.)Computer Power and Legal Language (pp. 39–60). New York: Quorum Books.
Berman, D. H. & Hafner, C. D. 1987. Indeterminacy: A Challenge to Logic-Based Models of Legal Reasoning,Yearbook of Law, Computers and Technology 3: 1–35.
Bowen, K. A. & Kowalski, R. A. 1982. Amalgamating Language and Metalanguage in Logic Programming. In K. L. Clark & S.-Å. Tärnlund (eds.)Logic Programming (pp. 153–172), London: Academic Press.
Bratley, P., Fremont, J., Mackaay, E. & Poulin D. 1991. Coping with Change. In Proceedings ofThe Third International Conference on Artificial Intelligence and Law, 69–75, Oxford: Association of Computing Machinery.
Clark, K. L. 1979. Predicate Logic as a Computational Formalism,Research Report 79/59, Department of Computing, Imperial College.
Eshghi, K. 1987.Meta-language in Logic Programming. Ph.D. Thesis, Department of Computing, Imperial College, London.
Hage, J. C., Leenes, R. & Lodder, A. R. 1994. Hard Cases: A Procedural Approach,J. Artificial Intelligence and Law 2: 113–167.
Hamfelt, A. 1990.The Multilevel Structure of Legal Knowledge and its Representation. Ph.L. Thesis, Uppsala University, Uppsala.
Hamfelt, A. 1992.Metalogic Representation of Multilayered Knowledge. Ph.D. Thesis, Uppsala University, Uppsala.
Hamfelt, A. & Barklund, J. 1989. Metalevels in Legal Knowledge and their Runnable Representation in Logic. In A. A. Martino (ed.) Pre-Proceedings ofThe Third International Congress, on Logic, Informatics, and Law, II, 557–576. Florence.
Hamfelt, A. & Barklund, J. 1990. Metaprogramming for Representation of Legal Principles. In M. Bruynooghe (ed.) Proceedings ofThe Second Workshop on Metaprogramming in Logic, 105–122, Katholieke Universiteit Leuven, Leuven.
Hamfelt, A. & Hansson, Å. 1991a. Metalogic Representation of Stratified Knowledge,UPMAIL TR 66, Computing Science Department, Uppsala University, Uppsala.
Hamfelt, A. & Hansson, Å. 1991b. Representation of Fragmentary and Multilayered Knowledge — a Semiformal Metatheory as an Interactive Metalogic Program,UPMAIL TR 68, Computing Science Department, Uppsala University, Uppsala.
Hamfelt, A. & Hansson, Å. 1992a. A Semiformal Metatheory for Fragmentary and Multilayered Knowledge as an Interactive Metalogic Program. In H. Tanaka (ed.) Proceedings ofThe International Conference on Fifth Generation Computer Systems, 1107–1114, Ohmsha, Tokyo.
Hamfelt, A. & Hansson, Å. 1992b. Representation of Fragmentary and Multilayered Knowledge. In A. Pettorossi (ed.): Meta-Programming in Logic, (pp. 321–335)Lecture Notes in Computer Science 649. Berlin: Springer-Verlag.
Hamfelt, A. & Fischer Nilsson, J. 1994. Inductive Metalogic Programming. In S. Wrobel (ed.) Proceedings ofThe Fourth International Workshop on Inductive Logic Programming, 85–96, GMD-Studien Nr. 237, ISSN 0170-8120, Bad Honnef/Bonn.
Hart, H. L. A. 1961.The Concept of Law. Oxford: Clarendon Press.
Horoviz, J. 1972.Law and Logic. Vienna: Springer-Verlag.
Kleene, S. C. 1980.Introduction to Metamathematics. New York: North-Holland.
Kowalski, R. A. & Sergot, M. J. 1990. The Use of Logical Models in Legal Problem Solving,Ratio Juris 3: 201–218.
Laird J. E., Newell, A. & Rosenbloom, P. S. 1987. SOAR: An Architecture for General Intelligence,J. Artificial Intelligence 33: 1–64.
Muggleton, S. & De Raedt, L. 1994. Inductive Logic Programming: Theory and Methods,J. Logic Programming 19, 20: 629–679.
Nitta, K., Nagao, J. & Mizutori, T. 1988. A Knowledge Representation and Inference System for Procedural Law,J. New Generation Computing 5: 319–359.
Poulin, D., Bratley, P., Frémont, J. & Mackaay E. 1993. Legal Interpretation in Expert Systems. In Proceedings ofThe Fourth International Conference on Artificial Intelligence and Law, 90–99, Amsterdam: Association of Computing Machinery.
Rosenbloom, P., Laird, J. & Newell, A. 1988. Meta-levels in Soar. In Maes, P. & Nardi, D. (eds.)Meta-Level Architectures and Reflection (pp. 227–240), Amsterdam: Elsevier Science Publishers B.V.
Schild, U. J. & Herzog, S. 1993. The Use of Meta-Rules in Rule Based Legal Computer Systems. In Proceedings ofThe Fourth International Conference on Artificial Intelligence and Law, 100–109, Amsterdam: Association of Computing Machinery.
Sergot, M. J. 1991. The Representation of Law in Computer Programs. In T. Bench-Capon (ed.)Knowledge-Based Systems and Legal Applications (pp. 3–67), London: Academic Press.
Skalak, D. B. & Rissland, E. L. 1992. Arguments and Cases: An Inevitable Intertwining,J. Artificial Intelligence and Law: 1: 3–44.
Tarski, A. 1944. The Semantic Conception of Truth,Philosophy and Phenomenological Research 4: 341–375.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Hamfelt, A. Formalizing multiple interpretation of legal knowledge. Artif Intell Law 3, 221–265 (1995). https://doi.org/10.1007/BF00871851
Issue Date:
DOI: https://doi.org/10.1007/BF00871851