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Evolving agents as a metaphor for the developing child
Author(s) -
Schlesinger Matthew
Publication year - 2004
Publication title -
developmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.801
H-Index - 127
eISSN - 1467-7687
pISSN - 1363-755X
DOI - 10.1111/j.1467-7687.2004.00333.x
Subject(s) - psychology , metaphor , cognitive science , typically developing , cognitive psychology , developmental psychology , linguistics , autism , philosophy
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.