Uncommon
Free energy principle
Hypothesis in neuroscience
Free energy principle
The free energy principle is a variational principle of self-organization from information physics. Its application to neurobiology suggests that the brain reduces surprise or uncertainty by making predictions based on generative models and uses sensory input to minimize variational free energy or, equivalently, maximize model evidence. This casts perception as Bayesian inference and action-perception cycles as active inference, where sensory feedback refines prediction-guided actions. Wide-ranging applications of the principle have addressed brain function, perception, and action. Its general applicability to living systems has been pursued.
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