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Evolution and connectionism

Published online by Cambridge University Press:  19 May 2011

Neil McNaughton
Neil McNaughton
Affiliation:
Department of Psychology, University of Otago, POB 56, Dunedin, New Zealand, Electronic mail: [email protected]
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Abstract

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Type
Continuing Commentary
Information
Behavioral and Brain Sciences , Volume 13 , Issue 2 , June 1990 , pp. 402 - 403
Copyright
Copyright © Cambridge University Press 1990

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References

Anderson, J. A., Silverstein, J. W., Ritz, S. A. & Jones, R. S. (1977) Distinctive features, categorical perception, and probability learning: Some applications of a neural model. Psychological Review 84:413–51. {DWM}CrossRefGoogle Scholar
Brousse, O. & Smolensky, P. (1989) Virtual memories and massive generalization in connectionist combinatorial learning. Proceedings of the Eleventh Annual Meeting of the Cognitive Science Society. Ann Arbor, Michigan. August. {rPS}Google Scholar
Chamberlin, T. (1965) The method of multiple working hypotheses. Science 148:754–59. {JAR}CrossRefGoogle ScholarPubMed
Collyer, C. E. (1985) Comparing strong and weak models by fitting them to computer-generated data. Perception and Psychophysics 38:476–81. {DWM}CrossRefGoogle ScholarPubMed
Derthick, M. & Plaut, D. C. (1986) Is distributed connectionism compatible with the physical symbol system hypothesis? Proceedings of the Eighth Annual Meeting of the Cognitive Science Society: 639–44. {DWM}Google Scholar
Elman, J. L. (1988) Finding structure in time. CRL Technical Report 8801. University of California, San Diego, Center for Research in Language. {rPS}Google Scholar
Estes, W. K. (1950) Toward a statistical theory of learning. Psychological Review 57:94–107. {DWM}CrossRefGoogle Scholar
(1982) Models of learning, memory, and choice: Selected papers. Praeger. {DWM}Google Scholar
Fodor, J. A. (1980) Methodological solipsism considered as a research strategy in cognitive sciences. In: The Behavioral and Brain Sciences. 3:63–109. {JRS}CrossRefGoogle Scholar
(1983) Modularity of mind. Bradford Books/MIT Press. {DWM}Google Scholar
Fodor, J. A. & Pylyshyn, Z. W. (1988) Connectionism and cognitive architecture: A critical analysis. Cognition 28:3–71. {rPS}CrossRefGoogle ScholarPubMed
Frisby, J. P. (1979) Seeing. Oxford University Press. {NM}Google Scholar
Gardner, H. (1985) The mind’s new science: A history of the cognitive revolution. Basic Books. {DWM}Google Scholar
Gentner, D. & Grudin, J. (1985) The evolution of mental metaphors in psychology: A 90-year retrospective. American Psychologist 40:181–92. {DWM}Google Scholar
George, F. & Johnson, L., eds. (1985) Purposive behaviour and teleological explanations. In: Studies in cybernetics, vol. 8. Gordon and Breach. {NM}Google Scholar
Geschwind, N. (1965) Disconnexion syndromes in animals and man. Brain 88:237–94. {JAR}CrossRefGoogle Scholar
Hebb, D. O. (1949) The organisation of behavior. John Wiley. {NM}Google Scholar
Hendler, J. (1987) Integrating marker-passing and problem solving. Lawrence Erlbaum. {JAR}Google Scholar
Hilgard, E. R. (1987) Psychology in America: A historical survey. Harcourt Brace Jovanovich. {DWM}Google Scholar
Lindsay, P. H. & Norman, D. A. (1972) Human information processing: An introduction to psychology. Academic Press. {DWM}Google Scholar
Llinas, R. R. & Simpson, J. I. (1981) Cerebellar control of movement. In: Handbook of behavioural neurobiology. Vol. 5: Motor coordination, ed. Towe, A. L. & Luschei, E. S.. Plenum Press. {NM}Google Scholar
Manicas, P. T. & Secord, P. F. (1983) Implications for psychology of the new philosophy of science. American Psychologist 38:399–413. {DWM}CrossRefGoogle Scholar
Marrocco, R. T. (1986) The neurobiology of perception. In: Mind and brain: Dialogues in cognitive neuroscience, ed. LeDoux, J. E. & Hirst, W.. Cambridge University Press. {DWM}Google Scholar
Massaro, D. W. (1986) Connectionist models of mind. Paper given at the twenty-seventh annual meeting of the Psychonomic Society, New Orleans. {DWM}Google Scholar
(1987) Speech perception by ear and eye: A paradigm for psychological inquiry. Lawrence Erlbaum. {DWM}Google Scholar
(1988) Some criticisms of connectionist models of human performance. Journal of Memory and Language 27:213–34. {DWM}CrossRefGoogle Scholar
(submitted) Testing between the TRACE model and the Fuzzy Logical Model of Speech Perception. Cognitive Psychology 21:398–421. {DWM}Google Scholar
Massaro, D. W. & Cohen, M. M. (1987) Process and connectionist models of pattern recognition. Proceedings of the Ninth Annual Conference of the Cognitive Science Society. Lawrence Erlbaum. {DWM}Google Scholar
McCarthy, John (1979) Ascribing mental qualities to machines. Stanford Artificial Intelligence Laboratory. Memo AIM-326. Computer Science Department. Report No. STAN-CS-79–725. {JRS}Google Scholar
McClelland, J. L. & Elman, J. L. (1986) The TRACE model of speech perception. Cognitive Psychology 18:1–86. {DWM}CrossRefGoogle ScholarPubMed
McClelland, J. L. & Kawamoto, A. H. (1986) Mechanisms of sentence processing: Assigning roles to constituents. In: Parallel distributed processing: Explorations in the microstructure of cognition. Vol. 2: Psychological and biological models, ed. McClelland, J. L., Rumelhart, D. E. & the PDP Research Group. Bradford Books/MIT Press. {rPS}Google Scholar
McClelland, J. L. & Rumelhart, D. E. (1981) An interactive activation model of context effects in letter perception: Part I. An account of basic findings. Psychological Review 88:375–407. {DWM}CrossRefGoogle Scholar
(1988) Explorations in parallel distributed processing: A handbook of models, programs, and exercises. MIT Press. {JRS}Google Scholar
McNaughton, B. L. & Morris, R. G. M. (1987) Hippocampal synaptic enhancement and information storage within a distributed memory system. Trends in Neuroscience 10:408–15. {rPS, NM}CrossRefGoogle Scholar
McNaughton, B. L. & Smolensky, P. (in press) Connectionist and neural modeling: Converging in the hippocampus. In: Cognitive neuroscience, ed. Weingartner, H. J. & Lister, R. G.. Oxford University Press. {rPS}Google Scholar
Miikkulainen, R. & Dyer, M. G. (1988) Encoding input/output representations in connectionist cognitive systems. In Proceedings of the connectionist summer school, 1988, ed. Touretzky, D. S., Hinton, G. E. & Sejnowski, T. J.. Morgan Kaufmann. {rPS}Google Scholar
Miller, J. (1982) Discrete versus continuous stage models of human information processing: In search of partial output. Journal of Experimental Psychology: Human Perception and Performance 8:273–96. {DWM}Google Scholar
Minsky, M. & Papert, S. (1969) Perceptrons. MIT Press. {DWM}Google Scholar
Monod, J. (1974) Chance and necessity. Fontana Books/William Collins. {NM}Google Scholar
Moore, J. W., Desmond, J. E., Berthier, N. E., Blazis, D. E. J., Sutton, R. S. & Barto, A. G. (1986) Behavioural Brain Research 21:143–54. {DWM}CrossRefGoogle Scholar
Mozer, M. C. (1988) A focused back-propagation algorithm for temporal pattern recognition. Technical Report CRG-TR-88–3. University of Toronto, Department of Computer Science, Connectionist Research Group. {rPS}Google Scholar
Neisser, U. (1967) Cognitive psychology. Appleton-Century-Crofts. {DWM}Google Scholar
Newell, Allen & Simon, Herbert A. (1976) Computer science as empirical inquiry: Symbols and search. In: Communications of the ACM. vol. 19, no. 2. {JRS}Google Scholar
Oden, G. C. (1979) A fuzzy logical model of letter identification. Journal of Experimental Psychology: Human Perception and Performance 5:336–52. {DWM}Google Scholar
(1984) Integration of fuzzy linguistic information in language comprehension. Fuzzy Sets and Systems 14:29–41. {GCO}Google Scholar
(1988) FuzzyProp: A symbolic superstrate for connectionist models. Proceedings of the IEEE International Conference on Neural Networks 2:293–301. {GCO}Google Scholar
Oden, G. C. & Massaro, D. W. (1978) Integration of featural information in speech perception. Psychological Review 85:172–91. {GCO}CrossRefGoogle ScholarPubMed
Pattee, H. (1977) Dynamic and linguistic modes of complex systems. International Journal of General Systems 3:259. {FJV}Google Scholar
Pellionisz, A. (1979) Modelling of neurons and neuronal networks. In: The neurosciences: Fourth study program, ed. Schmitt, F. O. & Worden, F. C.. MIT Press. {NM}Google Scholar
Peng, Y. & Reggia, J. (1987) A probabilistic causal model for diagnostic problem-solving. IEEE Transactions on Systems, Man and Cybernetics 17:146–62 and 395–406. {JAR}Google Scholar
(1989) A connectionist model for diagnostic modelling. IEEE Transactions on Systems, Man and Cybernetics 19:285–98. {JAR}CrossRefGoogle Scholar
Platt, J. R. (1964) Strong inference. Science 146:347–53. {DWM}CrossRefGoogle ScholarPubMed
Popper, K. (1959) The logic of scientific discovery. Basic Books. {DWM}Google Scholar
Pribram, K. H. (1986) The cognitive revolution and mind/brain issues. American Psychologist 41:507–20. {DWM}CrossRefGoogle ScholarPubMed
Pylyshyn, Z. W. (1984) Computation and cognition: Toward a foundation for cognitive science. Bradford Books/MIT Press. {VG, rPS}Google Scholar
Reggia, J. & Sutton, G. (1988) Self-processing networks and their biomedical implications. IEEE Proceedings 76:680–92. {JAR}Google Scholar
Rosenblatt, F. (1958) The perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review 65:386–407. {DWM}Google Scholar
(1962) Principles of neurodynamics. Spartan. {GCO}Google Scholar
Rosenblueth, A., Wiener, N. & Bigelow, J. (1943) Behavior, purpose and teleology. Philosophy of Science 10:18–24. {VG}CrossRefGoogle Scholar
Rueckl, J. G. (1986) A distributed connectionist model of letter and word identification. Ph.D. Thesis, University of Wisconsin. {GCO}Google Scholar
Rumelhart, D. E., Hinton, G. E. & McClelland, J. L. (1986) A general framework for parallel distributed processing. In: Parallel distributed processing, Vol. 1: Foundations, ed. Rumelhart, D. E. & McClelland, J. L.. MIT press. {DWM}Google Scholar
Rumelhart, D. E. & McClelland, J. L. (1986) On learning the past tenses of English verbs. In: Parallel distributed processing: Explorations in the microstructure of cognition. Vol. 2: Psychological and biological models, ed. McClelland, J. L., Rumelhart, D. E. & the PDF Research Group. Bradford Books/MIT Press. {rPS}Google Scholar
Schvaneveldt, R. W. & Meyer, D. E. (1973) Retrieval and comparison processes in semantic memory. In: Attention and performance, IV, ed. Kornblum, S.. Academic Press. {DWM}Google Scholar
Sejnowski, T. J. & Rosenberg, C. R. (1986) NETtalk: A parallel network that learns to read aloud. The Johns Hopkins University Electrical Engineering and Computer Science Technical Report, JHU/EECS-86/01. {DWM}Google Scholar
Selfridge, O. G. (1959) Pandemonium: A paradigm for learning. In: Mechanization of thought processes. Her Majesty’s Stationery Office. {DWM}Google Scholar
Servan-Schreiber, D., Cleeremans, A. & McClelland, J. L. (1988) Encoding sequential structure in simple recurrent networks. Technical Report CMU-CS-88–183. Carnegie-Mellon University, Department of Computer Science. {rPS}Google Scholar
Simon, H. A. (1962) The architecture of complexity. Proceedings of the American Philosophical Society 106:467–82. (Reprinted in Sciences in the artificial, 2d ed, MIT Press, 1981.) {VG}Google Scholar
(1973) The organization of complex systems. In: Hierarchy theory, ed. Pattee, H. H.. Braziller, G.. {VG}Google Scholar
(1977) How complex are complex systems? Proceedings of the 1976 Biennial Meeting of the Philosophy of Science Association 2:507–22. {rPS, VG}Google Scholar
Smolensky, P. (1986) Neural and conceptual interpretation of PDP models. In: Parallel distributed processing, Vol. 2: Psychological and biological models, ed. McClelland, J. L. & Rumelhart, D. E.. MIT press. {DWM}Google Scholar
(1987a) On variable binding and the representation of symbolic structures in connectionist systems. Technical Report CU-CS-355–87, Department of Computer Science, University of Colorado at Boulder. {rPS}Google Scholar
(1987b) The constituent structure of connectionist mental states: A reply to Fodor and Pylyshyn. Southern Journal of Philosophy 26 (Supplement):137–63. {rPS}Google Scholar
(1988) On the proper treatment of connectionism. Behavioral and Brain Sciences 11:1–74. {DWM}Google Scholar
(1989) Connectionism, constituency, and the language of thought. In: Jerry Fodor and his critics, ed. Loewer, B. & Rey, G.. Blackwell. {rPS}Google Scholar
(in press) Tensor product variable binding and the representation of symbolic structures in connectionist networks.Artificial Intelligence. {rPS}Google Scholar
(in preparation) Lectures on connectionist cognitive modeling. Erlbaum. {rPS}Google Scholar
Smolensky, P. & Rumelhart, D. E., eds. (in preparation) The mathematical foundations of neural network models. Erlbaum. {rPS}Google Scholar
Staddon, J. E. R. (1983) Adaptive behaviour and learning. Cambridge University Press. {NM}Google Scholar
Sternberg, S. (1975) Memory scanning: New findings and current controversies. Quarterly Journal of Experimental Psychology 27:1–32. {DWM}Google Scholar
Stone, G. O. (1988) From data to dynamics: The use of multiple levels of analysis. Behavioral and Brain Sciences 11:54–55. {rPS}CrossRefGoogle Scholar
Thorndike, E. L. (1898) Animal intelligence: An experimental study of the associative processes in animals. Psychological Review, Monograph Supplements, 2(Serial No. 8). {DWM}Google Scholar
Tweney, R. D., Doherty, M. E. & Mynatt, C. R., eds. (1981) On scientific thinking. Columbia University Press. {DWM}Google Scholar
Varela, F. (1979) Principles of biological autonomy. North-Holland. {FJV}Google Scholar
Varela, F., Dupire, B., Coutinho, A. & Vaz, N. (1988) Cognitive networks: Immune, neural and otherwise. In: Theoretical immunology, Vol. 2, ed. Perelson, A.. Addison-Wesley. {FJV}Google Scholar
Wald, J., Farach, M., Tagamets, M. & Reggia, J. (1989) Plausible diagnostic hypotheses with self-processing causal networks. Journal of Experimental and Theoretical Artificial Intelligence 1:91–112. {JAR}CrossRefGoogle Scholar