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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...
| Autores principales: | , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2009
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2760757/ https://www.ncbi.nlm.nih.gov/pubmed/19841749 http://dx.doi.org/10.1371/journal.pone.0007362 |