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Incorporating (variational) free energy models into mechanisms: the case of predictive processing under the free energy principle

Piekarski, Michał (2023) Incorporating (variational) free energy models into mechanisms: the case of predictive processing under the free energy principle. [Preprint]

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Abstract

The issue of the relationship between predictive processing (PP) and the free energy principle (FEP) remains a subject of debate and controversy within the research community. Many researchers have expressed doubts regarding the actual integration of PP with the FEP, questioning whether the FEP can truly contribute significantly to the mechanistic understanding of PP or even undermine such integration altogether. In this paper, I present an alternative perspective. I argue that, from the viewpoint of the constraint-based mechanisms approach, the FEP imposes an important constraint, namely variational free energy, on the mechanistic architecture proposed by PP. According to the constraint-based mechanisms approach, high-level cognitive mechanisms are integral parts of extensive heterarchical networks that govern the physiology and behavior of agents. Consequently, mechanistic explanations of cognitive phenomena should incorporate constraints and flows of free energy as relevant components, given that the implemented constraints operate as long as free energy is available. Within this framework, I contend that the FEP provides a relevant constraint for explaining at least some biological cognitive mechanisms described in terms of Bayesian generative models that minimize prediction errors.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Piekarski, Michałm.piekarski@uksw.edu.pl0000-0002-9482-526X
Additional Information: Forthcoming in "Synthese"
Keywords: predictive processing; mechanisms; explanation; constraints; free energy principle; variational free energy; realism; Bayesian inference; Bayesian mechanics; normativity.
Subjects: Specific Sciences > Computation/Information > Classical
Specific Sciences > Neuroscience > Cognitive Neuroscience
Specific Sciences > Cognitive Science > Computation
General Issues > Explanation
General Issues > Models and Idealization
General Issues > Philosophers of Science
Specific Sciences > Probability/Statistics
General Issues > Realism/Anti-realism
Depositing User: Dr Michał Piekarski
Date Deposited: 29 Jul 2023 20:29
Last Modified: 29 Jul 2023 20:29
Item ID: 22350
Subjects: Specific Sciences > Computation/Information > Classical
Specific Sciences > Neuroscience > Cognitive Neuroscience
Specific Sciences > Cognitive Science > Computation
General Issues > Explanation
General Issues > Models and Idealization
General Issues > Philosophers of Science
Specific Sciences > Probability/Statistics
General Issues > Realism/Anti-realism
Date: 29 July 2023
URI: https://philsci-archive-dev.library.pitt.edu/id/eprint/22350

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