Cargando…
Model-based learning retrospectively updates model-free values
Reinforcement learning (RL) is widely regarded as divisible into two distinct computational strategies. Model-free learning is a simple RL process in which a value is associated with actions, whereas model-based learning relies on the formation of internal models of the environment to maximise rewar...
Autores principales: | Doody, Max, Van Swieten, Maaike M. H., Manohar, Sanjay G. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8837618/ https://www.ncbi.nlm.nih.gov/pubmed/35149713 http://dx.doi.org/10.1038/s41598-022-05567-3 |
Ejemplares similares
-
Gambling on an empty stomach: Hunger modulates preferences for learned but not described risks
por: van Swieten, Maaike M. H., et al.
Publicado: (2023) -
Modeling the effects of motivation on choice and learning in the basal ganglia
por: van Swieten, Maaike M. H., et al.
Publicado: (2020) -
Hunger improves reinforcement-driven but not planned action
por: van Swieten, Maaike M.H., et al.
Publicado: (2021) -
Prosocial learning: Model-based or model-free?
por: Navidi, Parisa, et al.
Publicado: (2023) -
Model-based and model-free pain avoidance learning
por: Wang, Oliver, et al.
Publicado: (2018)