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Toward automatic constructive learning

Published online by Cambridge University Press:  26 June 2008

Thomas R. Shultz
Thomas R. Shultz
Affiliation:
Department of Psychology, McGill University, Montreal, Quebec H3A 1B1, Canada. thomas.shultz@mcgill.cawww.psych.mcgill.ca/perpg/fac/shultz/personal/default.htm
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Abstract

Neuroconstructivist modeling can be usefully extended with algorithms that build their own topology and recruit existing knowledge, effectively constructing a hierarchy of network modules. Possible benefits include allowing abilities to emerge naturally, in a way that affords objective study, deeper insights, and more rapid progress, and provides more serious consideration of the implications of constructivism.

Information

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 31 , Issue 3 , June 2008 , pp. 344 - 345
Copyright
Copyright © Cambridge University Press 2008

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