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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Detalles Bibliográficos
Autores principales: Kurth-Nelson, Zeb, Redish, A. David
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2009
Materias:
Research Article
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

Internet

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

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