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References
Ackley, D., Hinton, G. and Sejnowski, T. (1985), 'A learning algorithm for Boltzmann machines', Cognitive Science9, pp. 147–169.
Ashby, W. R. (1952), Design for a Brain, London: Chapman and Hall.
Beer, R. (2000), 'Dynamical approaches to cognitive science', Trends in Cognitive Sciences 4(3), pp. 91–99.
Crutchfield, J. (1998), 'Dynamical embodiments of computation in cognitive processes', The Behaviour and Brain Sciences21, p. 635.
Dennett, D. (1998), 'Revolution, no! Reform Si', Behavior and Brain Sciences21, pp. 636–637.
Elman, J. (1990), 'Finding structure in time', Cognitive Science14, pp. 179–211.
French, R. and Thomas, E. (1998), 'The dynamical hypothesis: One Battle Behind', The Behavior and Brain Sciences21(5), pp. 640–641.
Grossberg, S. (1976), 'Adaptive pattern classification and universal recoding: I. Parallel development and coding of neural feature detectors', Bioloical Cybernetics23, pp. 121–134.
Hebb, D.O. (1949), The Organization of Behavior, New York, NY: Wiley.
Hopfield, J. (1982), 'Neural networks and physical systems with emergent collective computational abilities', Proceedings of the National Academy of Sciences 7, pp. 2554–2558.
Hopfield, J. (1984), 'Neurons with graded response have collective computational properties like those of two-state neurons', Proceedings of the National Academy Sciences81, pp. 3088–3092.
Kaplan, S., Weaver, M. and French, R. (1991), 'Active Symbols and Internal Models: Towards a Cognitive Connectionism', AI and Society4(1), pp. 51–71. Reprinted in A. Clark and R. Lutz, eds., Connectionism in Context, Springer-Verlag, 1992, pp. 91-110.
Kohonen, T. (1982), 'Self-organized formation of topologically correct feature maps', Biological Cybernetics43, pp. 59–69.
Lakoff, G., (1986), Women, Fire and Dangerous Things, Cambridge, MA: MIT Press.
Minsky M and Papert, S. (1969), Perceptrons, Cambridge, MA: MIT Press.
Newell, A. and Simon, H. (1976), 'Computer science as empirical inquiry: Symbols and search', Communications of the ACM19, pp. 113–126.
Rapp P. (1993), 'Chaos in the neurosciences: cautionary tales from the frontier', Biologist40, pp. 89–94.
Rosenblatt, F. (1962), Principles of Neurodynamics. Perceptron and the Theory of Brain Mechanisms, Washington, D.C.: Spartan Books.
Rumelhart, D. and McClelland, J. (1986), Parallel Distributed Processing, Cambridge, MA: MIT Press.
Shastri, L. and Ajjanagadde, V. (1993), From simple associations to systematic reasoning: A connectionist representation of rules, variables, and dynamic bindings using temporal synchrony, Behavioral and Brain Science16, pp. 417–494.
Sougné, J. and French, R. (1997), 'A neurobiologically inspired model of working memory based on neuronal synchrony and rythmicity', in J. Bullinaria, G. Houghton, D. Glasspool, eds., Connectionist Representations: Proceedings of the Fourth Neural Computation and Psychology Workshop, Springer-Verlag, pp. 155–167.
Sougné, J. (2000), 'Binding and multiple instantiation in a distributed network of spiking nodes', Connection Science (in press).
Takens F. (1981), 'Detecting strange attractors in turbulence', in D.A. Rand and L.-S. Young, eds., Dynamical Systems and Turbulence, Springer-Verlag, New York, pp. 366–381.
Van Gelder, T. (1998), 'The dynamical hypothesis in cognitive science', The Behavior and Brain Sciences21, pp. 615–665.
Varela, F., Thompson. E. and Rosch, E. (1993), The Embodied Mind, Cambridge, MA: MIT Press.
Wiener, N. (1948), Cibernetics, New York: Wiley.
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French, R.M., Thomas, E. The Dynamical Hypothesis in Cognitive Science: A Review Essay of Mind As Motion. Minds and Machines 11, 101–111 (2001). https://doi.org/10.1023/A:1011256824648
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DOI: https://doi.org/10.1023/A:1011256824648