Cargando…
Correction: Computational modeling of choice-induced preference change: A Reinforcement-Learning-based approach
Autores principales: | Zhu, Jianhong, Hashimoto, Junya, Katahira, Kentaro, Hirakawa, Makoto, Nakao, Takashi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7935322/ https://www.ncbi.nlm.nih.gov/pubmed/33667283 http://dx.doi.org/10.1371/journal.pone.0248442 |
Ejemplares similares
-
Computational modeling of choice-induced preference change: A Reinforcement-Learning-based approach
por: Zhu, Jianhong, et al.
Publicado: (2021) -
Relation between choice-induced preference change and depression
por: Miyagi, Madoka, et al.
Publicado: (2017) -
Reinforcement Learning With Parsimonious Computation and a Forgetting Process
por: Toyama, Asako, et al.
Publicado: (2019) -
Correction: Linking Individual Learning Styles to Approach-Avoidance Motivational Traits and Computational Aspects of Reinforcement Learning
por: Aberg, Kristoffer Carl, et al.
Publicado: (2017) -
Post-response βγ power predicts the degree of choice-based learning in internally guided decision-making
por: Nakao, Takashi, et al.
Publicado: (2016)