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Литература

1161. Osborne M. J. and Rubinstein A. (1994) A Course in Game Theory. MIT Press, Cambridge,Massachusetts.

1162. Osherson D. N., Stob M., and Weinstein S. (1986) Systems That Learn: An Introduction to LearningTheory for Cognitive and Computer Scientists. MIT Press, Cambridge, Massachusetts.

1163. Page С D. and Srinivasan A. (2002) ILP: A short look back and a longer look forward. Submitted toJournal of Machine Learning Research.

1164. Рак I. (2001) On mixing of certain random walks, cutoff phenomenon and sharp threshold ofrandom matroid processes. DAMA TH: Discrete Applied Mathematics and Combinatorial Operations Research and Computer Science, 110, p. 251-272.

1165. Palay A. J. (1985) Searching with Probabilities. Pitman, London.

1166. Palmer D. A. and Hearst M. A. (1994) Adaptive sentence boundary disambiguation. In Proceedings ofthe Conference on Applied Natural Language Processing, p. 78—83. Morgan Kaufmann.

1167. Palmer S. (1999) Vision Science: Photons to Phenomenology. MIT Press, Cambridge, Massachusetts.

1168. Papadimitriou С. Н. (1994) Computational Complexity. Addison Wesley.

1169. Papadimitriou С H., Tamaki H., Raghavan P., and Vempala S. (1998) Latent semantic indexing:A probabilistic analysis. In Proceedings of the ACM Conference on Principles of Database Systems (PODS), p. 159-168, New York. ACM Press.

1170. Papadimitriou С H. and Tsitsiklis J. N. (1987) The complexity of markov decision processes.Mathematics of Operations Research, 12(3), p. 441-450.

1171. Papadimitriou С. Н. and Yannakakis M. (1991) Shortest paths without a map. Theoretical ComputerScience, 84(1), p. 127-150.

1172. Papavassiliou V. and Russell S. J. (1999) Convergence of reinforcement learning with generalfunction approximators. In Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI-99), p. 748-757, Stockholm. Morgan Kaufmann.

1173. Parekh R. and Honavar V. (2001) Dfa learning from simple examples. Machine Learning, 44, p. 9-35.

1174. Parisi G. (1988) Statistical field theory. Addison-Wesley, Reading, Massachusetts.

1175. Parker D. B. (1985) Learning logic. Technical report TR-47, Center for Computational Research inEconomics and Management Science, Massachusetts Institute of Technology, Cambridge, Massachusetts.

1176. Parker L. E. (1996) On the design of behavior-based multi-robot teams. Journal of Advanced Robotics, Щ6)1177. Parr R. and Russell S. J. (1998) Reinforcement learning with hierarchies of machines. In Jordan M.I., Kearns M., and Solla S. A. (Eds.), Advances in Neural Information Processing Systems 10. MIT Press, Cambridge, Massachusetts.

1178. Parzen E. (1962) On estimation of a probability density function and mode. Annals of MathematicalStatistics, 33, p. 1065-1076.

1179. Pasula H. and Russell S. J. (2001) Approximate inference for first-order probabilistic languages. InProceedings of the Seventeenth International Joint Conference on Artificial Intelligence (IJCAI-01), Seattle. Morgan Kaufmann.

1180. Pasula H., Russell S. J., Ostland M., and Ritov Y. (1999) Tracking many objects with many sensors.In Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI-99), Stockholm. Morgan Kaufmann.