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Evolutionary Schema of Modeling Based on Genetic Algorithms

learning. Boston, MA: Addison Wesley Holland, J. H. (1975). Adaptation in natural and artificial systems. Ann Arbor: University of Michigan Press. Michalewicz, Z. (1992). Genetic Alghorithms + Data Structures = Evolution Programs. Berlin: Springer Verlag. Michalewicz, Z. (1999). The significance of the evaluation function in evolutionary algorithms. In L. D. Davis, K. De Jong, M. D. Vose & L. D. Whitley (Eds.), Evolutionary Algorithms (Vol. 111 of The IMA Volumes in Mathematics and its Applications, pp. 151-166). New York

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Turing Machines and Evolution. A Critique of Gregory Chaitin’s Metabiology

References Alicea B. (2013), Metabiology and the Evolutionary Proof; available at: http://syntheticdaisies.blogspot.com/2013/01/metabiology-and-evolutionary-proof.html Baverstock, K. (2013), The role of information in cell regulation. [in:] Progress in Biophysics and Molecular Biology 111, pp. 141-143. Chaitin G. (2006), Epistemology as Information Theory: from Leibniz to [in:] Collapse, vol. 1, pp. 27-51. Chaitin G. (2007a), Algorithmic Information Theory: Some Recollections [in:] Randomness

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Unification Strategies in Cognitive Science

References Anderson, J. R. (2007). How Can the Mind Occur in the Physical Universe? Oxford: Oxford University Press. Arbib, M. A. (2005). From monkey-like action recognition to human language: An evolutionary framework for neurolinguistics. Behavioral and Brain Sciences, 28(2), 105-24-67. https://doi.org/10.1017/S0140525X05000038 Arbib, M. A. (2012). How the brain got language: the mirror system hypothesis. New York: Oxford University Press. Baddeley, A. D. (2000). The episodic buffer: A new

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