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E. Nisbett, The case of rules in reasoning. Cognitive Science, 16: 1–40, 1992. 67. M. W. ), What Computers Still Can’t Do: five reviews and a response. Artificial Intelligence, 80 (1): 95–191, 1996. 68. A. E. H. H. L. L. , Cambridge, Massachusetts: MIT Press, 1995. 69. S. E. Hinton, A distributed connectionist production system. Cognitive Science, 12: 423–466, 1988. 70. A. Turing, Computing Machinery and intelligence. Mind, 59: 433–460, 1950. 71. N. Wiener, Cybernetics: Or Control and Communication in the Animal and the Machine.

Oxford, UK: Blackwell, 1986. 12. L. Dreyfus, What Computers Still Can’t Do: A Critique of Artificial Reason. Cambridge, Massachusetts: MIT Press, 1992. 13. 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.

Visual knowledge is needed to determine objects from the background. Labeling blocks involves the use of spatial knowledge, such as layout of a typical document. Determining the font and identity of characters also involves spatial knowledge. Reading words in degraded text is a process that involves spatial as well as linguistic knowledge like a lexicon of acceptable words. ’’, is a process requiring spatial, syntactic, as well as semantic knowledge. Considerable interaction among different types of knowledge is necessary.

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


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