Temporal-difference reinforcement learning with distributed representations.
Temporal-difference (TD) algorithms have been proposed as models of reinforcement learning (RL). We examine two issues of distributed representation in these TD algorithms: distributed representations of belief and distributed discounting factors. Distributed representation of belief allows the beli...
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| Auteurs principaux: | , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Public Library of Science (PLoS)
2009
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/10b71edf81334d619f75d3ba97df1661 |
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