The Law of Practice and localist neural network models | NOVA. The University of Newcastle's Digital Repository

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/931285

Title: The Law of Practice and localist neural network models
Author/Creator: Heathcote, Andrew; Brown, Scott
Description: An extensive survey by Heathcote et al. (in press) found that the Law of Practice is closer to an exponential than a power form. We show that this result is hard to obtain for models using leaky competitive units when practice affects only the input, but that it can be accommodated when practice affects shunting self-excitation.
Relation: Behavioral and Brain Sciences Vol. 23, Issue 4, p. 479-480
Relation: http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=65541
Date: 2000
Publisher: Cambridge University Press
Keyword(s): Law of Practice; neural network models
Resource Type: journal article
Rights: uon-P146333-CPE13200061
Identifier: http://hdl.handle.net/1959.13/931285
Identifier: ISSN:0140-525X
Language: eng

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