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Литература

1121. Netto E. (1901) Lehrbuch derCombinatorik. B. G. Teubner, Leipzig.

1122. Nevill-Manning C. G. and Witten I. H. (1997) Identifying hierarchical structures in sequences:A linear-time algorithm. Journal of AI Research, 7, p. 67—82.

1123. Nevins A. J. (1975) Plane geometry theorem proving using forward chaining. Artificial Intelligence,5(1), p. 1-23.

1124. Newell A. (1982) The knowledge level. Artificial Intelligence, 18(\), p. 82-127.

1125. Newell A. (1990) Unified Theories of Cognition. Harvard University Press, Cambridge, Massachusetts.

1126. Newell A. and Ernst G. (1965) The search for generality. In Kalenich W. A. (Ed.), InformationProcessing 1965: Proceedings of IFIP Congress 1965, Vol. 1, p. 17-24, Chicago. Spartan.

1127. Newell A., Shaw J. C, and Simon H. A. (1957) Empirical explorations with the logic theorymachine. Proceedings of the Western Joint Computer Conference, 15, p. 218-239. Перепечатано в [459].

1128. Newell A., Shaw J. C, and Simon H. A. (1958) Chess playing programs and the problem ofcomplexity. IBM Journal of Research and Development, 4(2), p. 320-335.

1129. Newell A. and Simon H. A. (1961) GPS, a program that simulates human thought. In Billing H.(Ed.) Lernende Automaten, p. 109—124. R. Oldenbourg, Munich.

1130. Newell A. and Simon H. A. (1972) Human Problem Solving. Prentice-Hall, Upper Saddle River, NewJersey.

1131. Newell A. and Simon H. A. (1976) Computer science as empirical inquiry: Symbols and search.Communications of the Association for Computing Machinery, 19, p. 113-126.

1132. Newton I. (1664-1671) Methodus fluxionum et serierum infinitarum. Неопубликованные заметки.

1133. Ng A. Y., Harada D., and Russell S. J. (1999) Policy invariance under reward transformations:Theory and application to reward shaping. In Proceedings of the Sixteenth International Conference on Machine Learning, Bled, Slovenia. Morgan Kaufmann.

1134. Ng A. Y. and Jordan M. I. (2000) PEGASUS: A policy search method for large MDPs andPOMDPs. In Uncertainty in Artificial Intelligence: Proceedings of the Sixteenth Conference, p. 406-415, Stanford, California. Morgan Kaufmann.

1135. Nguyen X. and Kambhampati S. (2001) Reviving partial order planning. In Proceedings of theSeventeenth International Joint Conference on Artificial Intelligence (IJCAI-01), p. 459-466, Seattle. Morgan Kaufmann.

1136. Nguyen X., Kambhampati S., and Nigenda R. S. (2001) Planning graph as the basis for derivingheuristics for plan synthesis by state space and CSP search. Tech. rep., Computer Science and Engineering Department, Arizona State University.

1137. Nicholson A. and Brady J. M. (1992) The data association problem when monitoring robot vehiclesusing dynamic belief networks. In ECAI 92: 10th European Conference on Artificial Intelligence Proceeding?, p. 689-693, Vienna, Austria. Wiley.

1138. Niemela, I., Simons P., and Syrjanen T. (2000) Smodels: A system for answer set programming. InProceedings of the 8th International Workshop on Non-Monotonic Reasoning.

1139. Nilsson D. and Lauritzen S. (2000) Evaluating influence diagrams using LIMIDs. In Uncertainty inArtificial Intelligence: Proceedings of the Sixteenth Conference, p. 436—445, Stanford, California. Morgan Kaufmann.

1140. Nilsson N. J. (1965) Learning Machines: Foundations of Trainable Pattern-Classifying Systems.McGraw-Hill, New York, republished in 1990.