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The Law of Practice and localist neural network models
Citation
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
Abstract
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 and Cognitive Sciences |
| Research Group: | Cognitive Sciences |
| Research Field: | Decision Making |
| Objective Division: | Expanding Knowledge |
| Objective Group: | Expanding Knowledge |
| Objective Field: | Expanding Knowledge in Psychology and Cognitive Sciences |
| 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 |
| Downloads: | 0 |
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