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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http://dx.doi.org/10.1111/j.1467-7687.2004.00333.xDOI Listing

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