A Bayesian Foundation for Individual Learning Under Uncertainty

Computational learning models are critical for understanding mechanisms of adaptive behavior. However, the two major current frameworks, reinforcement learning (RL) and Bayesian learning, both have certain limitations. For example, many Bayesian models are agnostic of inter-individual variability an...

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Detalles Bibliográficos
Autores principales: Mathys, Christoph, Daunizeau, Jean, Friston, Karl J., Stephan, Klaas E.
Formato: Texto
Lenguaje:English
Publicado: Frontiers Research Foundation 2011
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3096853/
https://www.ncbi.nlm.nih.gov/pubmed/21629826
http://dx.doi.org/10.3389/fnhum.2011.00039

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3096853/
https://www.ncbi.nlm.nih.gov/pubmed/21629826
http://dx.doi.org/10.3389/fnhum.2011.00039

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