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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...

詳細記述

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書誌詳細
出版年:J Neurophysiol
主要な著者: Diederen, Kelly M. J., Schultz, Wolfram
フォーマット: Artigo
言語:Inglês
出版事項: American Physiological Society 2015
主題:
オンライン・アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC4563025/
https://ncbi.nlm.nih.gov/pubmed/26180123
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1152/jn.00483.2015
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