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43.Pattern Analysis and Machine Intelligence by John G. Webster (Editor) PDF

By John G. Webster (Editor)

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The Psychology of Computer Vision. New York: McGraw-Hill, 1975. 47. M. Minsky, The Society of Mind. New York: Simon & Schuster, 1985. 48. H. Moravec, Mind Children: The Future of Robot and Human Intelligence. Cambridge, Massachusetts: MIT Press, 1988. 49. A. A. A. Feigenbaum andJ. ), Computers and Thought. New York: McGraw-Hill, 1963. 50. A. J. Field, Sparse coding with an overcomplete basis set: a strategy employed by V1? Vision Research, 37: 3311–3325, 1997. 51. J. Pearl, Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.

New York: John Wiley & Sons, 1994. 3. G. ), Special volume “Artificial Intelligence in Perspective” of Artificial Intelligence, 59, (1–2), 1993. 4. A. ), The Philosophy of Artificial Intelligence. Oxford, UK: Oxford University Press, 1990. 5. A. ), Artificial Intelligence. San Diego, California: Academic Press, 1996. 6. A. Brooks, Cambrian Intelligence. Cambridge, Massachusetts: MIT Press, 1999. 7. A. Bundy, B. Silver, and D. Plummer, An analytical comparison of some rule-learning programs. Artificial Intelligence, 27(2): 137–181, 1985.

R. B. Scharf, Modeling novice-to-expert shifts in problem-solving strategy and knowledge organization. Cognitive Science, 14: 579–639, 1990. Artificial Intelligence 14. A. Ericsson andJ. ), Towards a General Theory of Expertise. New York: Cambridge University Press, 1991. 15. A. A. Simon, EPAM-like models of recognition and learning. Cognitive Science, 8: 305–336, 1984. 16. H. J. Pazzani, andP. ), Concept Formation: Knowledge and Experience in Unsupervised Learning. San Mateo, California: Morgan Kaufmann Publishers, 1991.

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43.Pattern Analysis and Machine Intelligence by John G. Webster (Editor)


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