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 REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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Bodenheimer (1974). Jurisprudence. Harvard University Press, Cambridge, MA.
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Bradshaw, G. (1987). Learning to recognize speech sounds' The nexus project. In Proceedings of the Fourth International IVorkshop on Machine Learning, pages 1-11.
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Branting, L. K. (1989). integrating generalizations with exemplar-based reasoning. In Proceedings of the Eleventh Annual Conference of the Cognitive Science Society, Ann Arbor, Michigan.
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Burton, S. J. (1985). An Introduction to Law and Legal Reasoning. Little, Brown and Company.
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Christie, G. C. (1969). Objectivity in law. }ttl~ Law journal, 78:1311-1350.
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Dietterich, T. G. and Michalski, R. S. (1983). A comparative review of selected methods for learning from examples. In Carbonell, J. G., Michalski, R. S., and Mitchell, T. M., editors, Machine Learning, volume 1, pages 41-81, 46. Tioga, Palo Alto, CA.
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Feinman, J. M. (1989). The jurisprudence of classification. Stanford Law Review, 41:661-717.
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Gentner, D. (1983). Structure mapping: A theoretical framework for analogy. Cognitive Science, 7(2):155-170.
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Goodhart, A. (1930). Determining the ratio decidendi of a case. Yale Law Review, 40:161.
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Goodhart, A. (1959). The ratio decidendi of a case. Modcrr~ Law Rcvlcw, 22.117.
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Itolyoak, K. and Thagard, P. (1989). Analogical mapping by constraint satisfaction. Cognitive Science, 13(3).
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Kolodner, J. (1988). Retrieving events from a case memory: A parallel implementation. In Proceedings of the DARPA Workshop on Casebased Reasoning, Clearwater, Florida. Morgan Kaufmann.
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Koton, P. (1988). Using Experience in Learning and Problem Solving. PhD thesis. ~Iassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
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McCarty, L. T. (1990). AI and law: I{ow to get there from here. In IVorkshop Notes of the Adversariat Reasoning and Artificial Intelligence and Legal Reasoning tVorkshop of the Eighth National Conference on Artificial Intelligence.
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McCarty, L. T. and Sridharan, N. S. (1982). A computational theory of legal argument. Technical Report LRP-TR-13, Laboratory for Computer Science Research, Rutgers University.
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Redmond, M. (1990). Distributed cases for casebased reasoning; facilitating use of multiple cases, in Proceedings of AAAL90, Boston. American Association for Artificial Intelligence.
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Rissland, E. L. (1990). Artificial intelligence and law: Stepping stones to a model of legal reasoning. Yale Law Review, 99'1957-1981.
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Rosch, E. and Mervis, C. B. (1975). Family resemblance: Studies in the internal structure of categories. Cognitive Psychology, 7:573-605.
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Salzberg, S. (1988). Exemplar-based learning: theory and implementation. Technical Report TR-10-88, Center for Research in Computing Technology, Harvard University.
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