An Active Inference Approach to Modeling Structure Learning: Concept Learning as an Example Case

An Active Inference Approach to Modeling Structure Learning: Concept Learning as an Example Case

Within computational neuroscience, the algorithmic and neural basis of structure learning remains poorly understood. Concept learning is one primary example, which requires both a type of internal model expansion process (adding novel hidden states that explain new observations), and a model reducti...

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Bibliographic Details
Main Authors: Ryan Smith, Philipp Schwartenbeck, Thomas Parr, Karl J. Friston
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-05-01
Series:Frontiers in Computational Neuroscience
Subjects:
Bayesian model expansion
Bayesian model reduction
structure learning
concepts
computational neuroscience
active inference
Online Access:https://www.frontiersin.org/article/10.3389/fncom.2020.00041/full

Internet

https://www.frontiersin.org/article/10.3389/fncom.2020.00041/full

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