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Литература

641. Heckerman D. (1998) A tutorial on learning with Bayesian networks. In Jordan M. I. (Ed.), Learningin graphical models. Kluwer, Dordrecht, Netherlands.

642. Heckerman D., Geiger D., and Chickering D. M. (1994) Learning Bayesian networks: Thecombination of knowledge and statistical data. Technical report MSR-TR-94-09, Microsoft Research, Redmond, Washington.

643. Heim I. and Kratzer A. (1998) Semantics in a Generative Grammar. Blackwell, Oxford, UK.

644. Heinz E. A. (2000) Scalable search in computer chess. Vieweg, Braunschweig, Germany.

645. Held M. and Karp R. M. (1970) The traveling salesman problem and minimum spanning trees.Operations Research, 18, p. 1138-1162.

646. Helmert M. (2001) On the complexity of planning in transportation domains. In Cesta A. and BarrajoD. (Eds.), Sixth European Conference on Planning (ECP-01), Toledo, Spain. Springer-Verlag.

647. Hendrix G. G. (1975) Expanding the utility of semantic networks through partitioning. In Proceedingsof the Fourth International Joint Conference on Artificial Intelligence (IJCAI-75), p. 115-121, Tbilisi, Georgia. IJCAII.

648. Henrion M. (1988) Propagation of uncertainty in Bayesian networks by probabilistic logic sampling.In Lemmer J. F. and Kanal L. N. (Eds.), Uncertainty in Artificial Intelligence 2, p. 149-163. Elsevier/North-Holland, Amsterdam, London, New York.

649. Henzinger T. A. and Sastry S. (Eds.) (1998) Hybrid systems: Computation and control. Springer-Verlag,Berlin.

650. Herbrand J. (1930) Recherches sur la Theorie de la Demonstration. Ph.D. thesis, University of Paris.

651. Hewitt C. (1969) PLANNER: a language for proving theorems in robots. In Proceedings of the FirstInternational Joint Conference on Artificial Intelligence (IJCAI-69), p. 295-301, Washington, DC. IJCAII.

652. Hierholzer С (1873) Uber die Moglichkeit einen Linienzug ohne Wiederholung und ohneUnterbrechung zu umfahren. Mathematische Annalen, 6, p. 30—32.

653. Hilgard E. R. and Bower G. H. (1975) Theories of Learning (4th edition). Prentice-Hall, Upper SaddleRiver, New Jersey.

654. Hintikka J. (1962) Knowledge and Belief. Cornell University Press, Ithaca, New York.

655. Hinton G. E. and Anderson J. A. (1981) Parallel Models of Associative Memory. Lawrence ErlbaumAssociates, Potomac, Maryland.

656. Hinton G. E. and Nowlan S. J. (1987) How learning can guide evolution. Complex Systems, 1(3),p. 495-502.

657. Hinton G. Ε. and Sejnowski T. (1983) Optimal perceptual inference. In Proceedings of the IEEEComputer Society Conference on Computer Vision and Pattern Recognition, p. 448—453, Washington, DC. IEEE Computer Society Press.

658. Hinton G. E. and Sejnowski T. (1986) Learning and relearning in Boltzmann machines. In RumelhartD. E. and McClelland J. L. (Eds.), Parallel Distributed Processing, chap. 7, p. 282-317. MIT Press, Cambridge, Massachusetts.

659. Hirsh H. (1987) Explanation-based generalization in a logic programming environment. In Proceedings of theTenth International Joint Conference on Artificial Intelligence (IJCAI-87), Milan. Morgan Kaufmann.

660. Hirst G. (1981) Anaphora in Natural Language Understanding: A Survey, Vol. 119 of Lecture Notes inComputer Science. Springer Verlag, Berlin.