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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...
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| Hauptverfasser: | , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Public Library of Science
2009
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2760757/ https://ncbi.nlm.nih.gov/pubmed/19841749 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0007362 |
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