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Литература

1101.  Muggleton S. H. and De Raedt L. (1994) Inductive logic programming: Theory and methods. Journalof Logic Programming, 19/20, p. 629-679.

1102. Muggleton S. H. and Feng C. (1990) Efficient induction of logic programs. In Proceedings of theWorkshop on Algorithmic Learning Theory, p. 368-381, Tokyo. Ohmsha.

1103. Muller M. (2002) Computer Go. Artificial Intelligence, 134(1-2), p. 145-179.

1104. Mundy J. and Zisserman A. (Eds.) (1992) Geometric Invariance in Computer Vision. MIT Press,Cambridge, Massachusetts.

1105. Murphy K., Weiss Y., and Jordan M. I. (1999) Loopy belief propagation for approximate inference:Ал empirical study. In Uncertainty in Artificial Intelligence: Proceedings of the Fifteenth Conference, p. 467-475, Stockholm. Morgan Kaufmann.

1106. Murphy K. and Russell S. J. (2001) Rao-blackwellised particle filtering for dynamic bayesiannetworks. In Doucet A., de Freitas N., and Gordon N. J. (Eds.) Sequential Monte Carlo Methods in Practice. Springer-Verlag, Berlin.

1107. Murphy R. (2000) Introduction to AIRobotics. MIT Press, Cambridge, Massachusetts.

1108. Muscettola N., Nayak P., Pell В., and Williams B. (1998) Remote agent: To boldly go where no aisystem has gone before. Artificial Intelligence, 103, p. 5-48.

1109. Myerson R. B. (1991) Game Theory: Analysis of Conflict. Harvard University Press, Cambridge.

1110. Nagel T. (1974) What is it like to be a bat? Philosophical Review, 83, p. 435-450.

1111. Nalwa V. S. (1993) A Guided Tour of Computer Vision. Addison-Wesley, Reading, Massachusetts.

1112. Nash J. (1950) Equilibrium points in N-person games. Proceedings of the National Academy ofSciences of the United States of America, 36, p. 48—49.

1113. Nau D. S. (1980) Pathology on game trees: A summary of results. In Proceedings of the First AnnualNational Conference on Artificial Intelligence (AAAI-80), p. 102—104, Stanford, California. AAAI.

1114. Nau D. S. (1983) Pathology on game trees revisited, and an alternative to minimaxing. ArtificialIntelligence, 27(1-2), p. 221-244.

1115. Nau D. S., Kumar V., and Kanal L. N. (1984) General branch and bound, and its relation to A* andКО*. Artificial Intelligence, 23, p. 29-58.

1116. Naur P. (1963) Revised report on the algorithmic language Algol 60. Communications of theAssociation for Computing Machinery, 6{ 1), p. 1—17.

1117. Nayak P. and Williams B. (1997) Fast context switching in real-time propositional reasoning. InProceedings of the Fourteenth National Conference on Artificial Intelligence (AAAI-97), p. 50-56, Providence, Rhode Island. AAAI Press.

1118. Neal R. (1996) Bayesian Learning for Neural Networks. Springer-Verlag, Berlin.

1119. Nebel B. (2000) On the compilability and expressive power of propositional planning formalisms.Journal ofAI Research, 12, p. 271 -315.

1120. Nelson G. and Oppen D. С (1979) Simplification by cooperating decision procedures. ACMTransactions on Programming Languages and Systems, 1(2), p. 245—257.