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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Detalles Bibliográficos
Autores principales: Nakano, Takashi, Otsuka, Makoto, Yoshimoto, Junichiro, Doya, Kenji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4347982/
https://www.ncbi.nlm.nih.gov/pubmed/25734662
http://dx.doi.org/10.1371/journal.pone.0115620

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4347982/
https://www.ncbi.nlm.nih.gov/pubmed/25734662
http://dx.doi.org/10.1371/journal.pone.0115620

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