Shultz, T. R. (2003). Computational explorations of cognitive development. Proceedings of the Twenty-fifth Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum.

 

Abstract

Considerable leverage on basic issues in development can be gained by applying computational modeling, particularly with artificial neural networks. The cascade-correlation algorithm has been applied to a variety of developmental phenomena including the balance scale, conservation, seriation, personal pronouns, discrimination shift learning, habituation of attention, concept acquisition, and concepts of velocity, time, and distance. The simulations clarify a number of longstanding developmental issues such as knowledge representation, representation change, stage sequences, transition, the possibility of constructivism, the presence of perceptual effects in cognitive tasks, emergence of non-normative rules, and the trajectory of development.

 

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