Evolving agents as a metaphor for the developing child.

Matthew Schlesinger

doi:10.1111/j.1467-7687.2004.00333.x

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Evolving agents as a metaphor for the developing child.

Matthew Schlesinger

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Abstract

The emerging field of Evolutionary Computation (EC), inspired by neo-Darwinian principles (e.g. natural selection, mutation, etc. ), offers developmental psychologists a wide array of mathematical tools for simulating ontogenetic processes. In this brief review; I begin by highlighting three of the approaches that EC researchers employ (Artificial Life, evolutionary robotics and comparative stochastic optimization). I then focus on the advantages of using comparative stochastic optimization as a method for studying development. As a concrete example, I illustrate the design and implementation of an EC model that simulates the development of reaching in young infants.

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Animals Artificial Intelligence Biological Evolution Child Child Development Child, Preschool Computer Simulation Developmental Biology Genetics, Population Humans Infant Metaphor Models, Genetic Selection, Genetic Stochastic Processes Journal Article Research Support, U.S. Gov't, P.H.S.Review

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Matthew Schlesinger. 2004. Evolving agents as a metaphor for the developing child.. https://doi.org/10.1111/j.1467-7687.2004.00333.x

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