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The Law of Practice and localist neural network models


Heathcote, A and Brown, S, The Law of Practice and localist neural network models, Behavioral and Brain Sciences, 23, (4) pp. 479-480. ISSN 0140-525X (2000) [Contribution to Refereed Journal]

DOI: doi:10.1017/S0140525X00353353


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.

Item Details

Item Type:Contribution to Refereed Journal
Research Division:Psychology
Research Group:Cognitive and computational psychology
Research Field:Decision making
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in psychology
UTAS Author:Heathcote, A (Professor Andrew Heathcote)
ID Code:99776
Year Published:2000
Web of Science® Times Cited:3
Deposited By:Medicine
Deposited On:2015-04-09
Last Modified:2015-05-11

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