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Decomposing the effects of context valence and feedback information on speed and accuracy during reinforcement learning: a meta-analytical approach using diffusion decision modeling
Reinforcement learning (RL) models describe how humans and animals learn by trial-and-error to select actions that maximize rewards and minimize punishments. Traditional RL models focus exclusively on choices, thereby ignoring the interactions between choice preference and response time (RT), or how...
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| Publicado no: | Cogn Affect Behav Neurosci |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Springer US
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6598978/ https://ncbi.nlm.nih.gov/pubmed/31175616 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3758/s13415-019-00723-1 |
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