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Asymmetric and adaptive reward coding via normalized reinforcement learning
Learning is widely modeled in psychology, neuroscience, and computer science by prediction error-guided reinforcement learning (RL) algorithms. While standard RL assumes linear reward functions, reward-related neural activity is a saturating, nonlinear function of reward; however, the computational...
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Public Library of Science
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9345478/ https://www.ncbi.nlm.nih.gov/pubmed/35862443 http://dx.doi.org/10.1371/journal.pcbi.1010350 |