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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Bibliographic Details
Main Authors: Christoph eMathys, Jean eDaunizeau, Karl J Friston, Klaas Enno Stephan
Format: Article
Language:English
Published: Frontiers Media S.A. 2011-05-01
Series:Frontiers in Human Neuroscience
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnhum.2011.00039/full