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Computational mechanisms underlying motivation to earn symbolic reinforcers
Reinforcement learning (RL) is a theoretical framework that describes how agents learn to select options that maximize rewards and minimize punishments over time. We often make choices, however, to obtain symbolic reinforcers (e.g. money, points) that can later be exchanged for primary reinforcers (...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Cold Spring Harbor Laboratory
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10592730/ https://www.ncbi.nlm.nih.gov/pubmed/37873311 http://dx.doi.org/10.1101/2023.10.11.561900 |