Scaling prediction errors to reward variability benefits error-driven learning in humans

Effective error-driven learning requires individuals to adapt learning to environmental reward variability. The adaptive mechanism may involve decays in learning rate across subsequent trials, as shown previously, and rescaling of reward prediction errors. The present study investigated the influenc...

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Detalles Bibliográficos
Autores principales: Diederen, Kelly M. J., Schultz, Wolfram
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Physiological Society 2015
Materias:
Higher Neural Functions and Behavior
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4563025/
https://www.ncbi.nlm.nih.gov/pubmed/26180123
http://dx.doi.org/10.1152/jn.00483.2015

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4563025/
https://www.ncbi.nlm.nih.gov/pubmed/26180123
http://dx.doi.org/10.1152/jn.00483.2015

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