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A Spiking Neural Network Model of Model-Free Reinforcement Learning with High-Dimensional Sensory Input and Perceptual Ambiguity
A theoretical framework of reinforcement learning plays an important role in understanding action selection in animals. Spiking neural networks provide a theoretically grounded means to test computational hypotheses on neurally plausible algorithms of reinforcement learning through numerical simulat...
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| Publicado en: | PLoS One |
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| Autores principales: | , , , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
Public Library of Science
2015
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4347982/ https://ncbi.nlm.nih.gov/pubmed/25734662 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0115620 |
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