Dissociation between asymmetric value updating and perseverance in human reinforcement learning

Abstract The learning rate is a key parameter in reinforcement learning that determines the extent to which novel information (outcome) is incorporated in guiding subsequent actions. Numerous studies have reported that the magnitude of the learning rate in human reinforcement learning is biased depe...

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Autores principales: Michiyo Sugawara, Kentaro Katahira
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/bd93cbb47f574d3f9424c9e878b5b931
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