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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...
Uloženo v:
| Vydáno v: | Cogn Affect Behav Neurosci |
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| Hlavní autoři: | , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Springer US
2019
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| Témata: | |
| On-line přístup: | 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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