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Литература

281. Collins M. J. (1996) A new statistical parser based on bigram lexical dependencies. In Joshi A. K. andPalmer M. (Eds.), Proceedings of the Thirty-Fourth Annual Meeting of the Association for Computational Linguistics, p. 184—191, San Francisco. Morgan Kaufmann Publishers.

282. Collins M. J. (1999) Head-driven Statistical Models for Natural Language Processing. Ph.D. thesis,University of Pennsylvania.

283. Collins M. and Duffy K. (2002) New ranking algorithms for parsing and tagging: Kernels over discretestructures, and the voted perceptron. In Proceedings of the ACL.

284. Colmerauer A. (1975) Les grammaires de metamorphose. Tech. rep., Groupe d'IntelligenceArtificielle, Universite de Marseille-Luminy.

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286. Condon J. H. and Thompson K. (1982) Belle chess hardware. In Clarke M. R. B. (Ed.), Advances inComputer Chess 3, p. 45-54. Pergamon, Oxford, UK.

287. Congdon С. В., Huber M., Kortenkamp D., Bidlack C, Cohen C, Huffman S., Koss F., Raschke U.,and Weymouth T. (1992) CARMEL versus Flakey: A comparison of two robots. Tech. rep. Papers from the AAA! Robot Competition, RC-92-01, American Association for Artificial Intelligence, Menlo Park, CA.

288. Connell J. (1989) A Colony Architecture for an Artificial Creature. Ph.D. thesis, Artificial IntelligenceLaboratory, MIT, Cambridge, MA. Предоставляется также под названием AI Technical Report 1151.

289. Cook S. A. (1971) The complexity of theorem-proving procedures. In Proceedings of the 3rd AnnualACM Symposium on Theory of Computing, p. 151-158, New York. ACM Press.

290. Cook S. A. and Mitchell D. (1997) Finding hard instances of the satisfiability problem: A survey. InDu D., Gu J., and Pardalos P. (Eds.), Satisfiability problems: Theory and applications. American Mathematical Society, Providence, Rhode Island.

291. Cooper G. (1990) The computational complexity of probabilistic inference using Bayesian beliefnetworks. Artificial Intelligence, 42, p. 393-405.

292. Cooper G. and Herskovits E. (1992) A Bayesian method for the induction of probabilistic networksfrom data. Machine Learning, 9, p. 309-347.

293. Copeland J. (1993) Artificial Intelligence: A Philosophical Introduction. Blackwell, Oxford, UK.

294. Copernicus (1543) De Revolutionibus Orbium Coelestium. Apud Ioh. Petreium, Nuremberg.

295. Cormen Т. Н., Leiserson С. Е., and Rivest R. (1990) Introduction to Algorithms. MIT Press,Cambridge, Massachusetts.

296. Cortes C. and Vapnik V. N. (1995) Support vector networks. Machine Learning, 20, p. 273-297.

297. Cournot A. (Ed.) (1838) Recherches sur les principes mathematiques de la theorie des richesses.L. Hachette, Paris.

298. Covington M. A. (1994) Natural Language Processing for Prolog Programmers. Prentice-Hall, UpperSaddle River, New Jersey.

299. Cowan J. D. and Sharp D. H. (1988a) Neural nets. Quarterly Reviews of Biophysics, 21, p. 365-427.

300. Cowan J. D. and Sharp D. H. (1988b) Neural nets and artificial intelligence. Daedalus, 117, p. 85-121.