741. Johnston M. D. and Adorf H.-M. (1992) Scheduling with neural networks: The case of the Hubblespace telescope. Computers & Operations Research, 79(3-4), p. 209-240.

742. Jones N. D., Gomard С. К., and Sestoft P. (1993) Partial Evaluation and Automatic ProgramGeneration. Prentice-Hall, Upper Saddle River, New Jersey.

743. Jones R., Laird J. E., and Nielsen P. E. (1998) Automated intelligent pilots for combat flightsimulation. In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98), p. 1047-54, Madison, Wisconsin. AAAI Press.

744. Jonsson A., Morris P., Muscettola N., Rajan K., and Smith B. (2000) Planning in interplanetaryspace: Theory and practice. In Proceedings of the 5th International Conference on Artificial Intelligence Planning Systems (AIPS-00), p. 177-186, Breckenridge, Colorado. AAAI Press.

745. Jordan M. I. (1995) Why the logistic function? a tutorial discussion on probabilities and neuralnetworks. Computational cognitive science technical report 9503, Massachusetts Institute of Technology.

746. Jordan M. I. (2003) An Introduction to Graphical Models. В печати.

747. Jordan M I., Ghahramani Z., Jaakkola Т., and Saul L. K. (1998) An introduction to variationalmethods for graphical models. In Jordan M. I. (Ed.) Learning in Graphical Models. Kluwer, Dordrecht, Netherlands.

748. Jordan M. I., Ghahramani Z., Jaakkola Т., and Saul L. K. (1999) An introduction to variationalmethods for graphical models. Machine Learning, 37(2—3), p. 183-233.

749. Joshi A. K. (1985) Tree-adjoining grammars: How much context sensitivity is required to providereasonable structural descriptions. In Dowty D., Karttunen L., and Zwicky A. (Eds.) Natural Language Parsing. Cambridge University Press, Cambridge, UK.

750. Joshi A. K., Webber B. L., and Sag I. (1981) Elements of Discourse Understanding. CambridgeUniversity Press, Cambridge, UK.

751. Joslin D. and Pollack M. E. (1994) Least-cost flaw repair: A plan refinement strategy for partial-orderplanning. In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), p. 1506, Seattle. AAAI Press.

752. Jouannaud J.-P. and Kirchner C. (1991) Solving equations in abstract algebras: A rule-based survey ofunification. In Lassez J.-L. and Plotkin G. (Eds.), Computational Logic, p. 257-321. MIT Press, Cambridge, Massachusetts.

753. Judd J. S. (1990) Neural Network Design and the Complexity of Learning. MIT Press, Cambridge,Massachusetts.

754. Juels A. and Wattenberg M. (1996) Stochastic hillclimbing as a baseline method for evaluating geneticalgorithms. In Touretzky D. S., Mozer M. C, and Hasselmo M. E. (Eds.) Advances in Neural Information Processing Systems, Vol. 8, p. 430—436. MIT Press, Cambridge, Massachusetts.

755. Julesz B. (1971) Foundations of Cyclopean Perception. University of Chicago Press, Chicago.

756. Jurafsky D. and Martin J. H. (2000) Speech and Language Processing: An Introduction to NaturalLanguage Processing, Computational Linguistics, and Speech Recognition. Prentice-Hall, Upper Saddle River, New Jersey.

757. Kadane J. B. and Larkey P. D. (1982) Subjective probability and the theory of games. ManagementScience, 28(2), p. 113-120.

758. Kaelbling L. P., Littman M. L., and Cassandra A. R. (1998) Planning and action in partiallyobservable stochastic domains. Artificial Intelligence, 101, p. 99-134.

759. Kaelbling L. P., Littman M. L., and Moore A. W. (1996) Reinforcement learning: A survey. Journal ofArtificial Intelligence Research, 4, p. 237-285.

760. Kaelbling L. P. and Rosenschein S. J. (1990) Action and planning in embedded agents. Robotics andAutonomous Systems, 5(1-2), p. 35-48.