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Литература

921. Levy D. N. L. (Ed.) (1988b) Computer Games. Springer-Verlag, Berlin.

922. Lewis D. D. (1998) Naive Bayes at forty: The independence assumption in information retrieval. In MachineLearning: ECML-98. 10th European Conference on Machine Learning. Proceedings, p. 4-15, Chemnitz, Germany. Springer-Verlag.

923. Lewis D. K. (1966) An argument for the identity theory. The Journal of Philosophy, 63(1), p. 17-25.

924. Lewis D. K. (1972) General semantics. In Davidson D. and Harman G. (Eds.), Semantics of NaturalLanguage, p. 169-218. D. Reidel, Dordrecht, Netherlands.

925. Lewis D. K. (1980) Mad pain and Martian pain. In Block N. (Ed.), Readings in Philosophy ofPsychology, Vol. 1, p. 216-222. Harvard University Press, Cambridge, Massachusetts.

926. Li С. М. and Anbulagan (1997) Heuristics based on unit propagation for satisfiability problems. InProceedings of the Fifteenth International Joint Conference on Artificial Intelligence (IJCAI-97), p. 366—371, Nagoya, Japan. Morgan Kaufmann.

927. Li M. and Vitanyi P. M. B. (1993) An Introduction to Kolmogorov Complexity and Its Applications.Springer-Verlag, Berlin.

928. Lifschitz V. (1986) On the semantics of STRIPS. In Georgeff M. P. and Lansky A. L. (Eds.),Reasoning about Actions and Plans: Proceedings of the 1986 Workshop, p. 1-9, Timberline, Oregon. Morgan Kaufmann.

929. Lifschitz V. (2001) Answer set programming and plan generation. Artificial Intelligence, 138(1-2), p. 39-54.

930. Lighthill J. (1973) Artificial intelligence: A general survey. In Lighthill J., Sutherland N. S., NeedhamR. M., Longuet-Higgins H. C, and Michie D. (Eds.), Artificial Intelligence: A Paper Symposium. Science Research Council of Great Britain, London.

931. Lin F. and Reiter R. (1997) How to progress a database. Artificial Intelligence, 92(1—2), p. 131-167.

932. Lin S. (1965) Computer solutions of the travelling salesman problem. Bell Systems Technical Journal,44(10), 2245-2269.

933. Lin S. and Kernighan B. W. (1973) An effective heuristic algorithm for the travelling-salesmanproblem. Operations Research, 27(2), p. 498-516.

934. Linden T. A. (1991) Representing software designs as partially developed plans. In Lowry M. R. andMcCartney R. D. (Eds.), Automating Software Design, p. 603-625. MIT Press, Cambridge, Massachusetts.

935. Lindsay R. K. (1963) Inferential memory as the basis of machines which understand natural language.In Feigenbaum E. A. and Feldman J. (Eds.), Computers and Thought, p. 217—236. McGraw-Hill, New York.

936. Lindsay R. K., Buchanan B. G., Feigenbaum E. A., and Lederberg J. (1980) Applications of ArtificialIntelligence for Organic Chemistry: The DENDRAL Project. McGraw-Hill, New York.

937. Littman M. L. (1994) Markov games as a framework for multi-agent reinforcement learning. InProceedings of the 11th International Conference on Machine Learning (ML-94), p. 157—163, New Brunswick, NJ. Morgan Kaufmann.

938. Littman M. L., Keim G. A., and Shazeer N. M. (1999) Solving crosswords with PROVERB. InProceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99), p. 914—915, Orlando, Florida. AAAI Press.

939. Liu J. S. and Chen R. (1998) Sequential Monte Carlo methods for dynamic systems. Journal of theAmerican Statistical Association, 93, p. 1022—1031.

940. Lloyd J. W. (1987) Foundations of Logic Programming. Springer-Verlag, Berlin.