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Dopaminergic Balance between Reward Maximization and Policy Complexity
Previous reinforcement-learning models of the basal ganglia network have highlighted the role of dopamine in encoding the mismatch between prediction and reality. Far less attention has been paid to the computational goals and algorithms of the main-axis (actor). Here, we construct a top-down model...
| Autores principales: | , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Research Foundation
2011
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3093748/ https://www.ncbi.nlm.nih.gov/pubmed/21603228 http://dx.doi.org/10.3389/fnsys.2011.00022 |