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

Piekarski, Michał (2022) Incorporating free energy models into mechanisms: the case of predictive processing under the free energy principle. [Preprint]

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Abstract

There is a view emerging in the philosophy of science that research practices in science can be characterized in terms of discovering and describing mechanisms. Mechanistic explanations are based on the identifying the underlying mechanisms that generate a target phenomenon and strategies understood as decomposition of these mechanisms. Recently, there has been a discussion among mechanists about the necessity to include constraints and free energy flows into the explanations, as constitutive components of mechanistic explanations. This is directly related to the existence of control mechanisms that are non-autonomous and entail the existence of heterarchical networks. I refer to this as the ‘constrained mechanisms approach’. This paper examines the extent to which this approach can be applied to the predictive processing framework, which is now an influential process theory, offering a computational description of perceptual and cognitive mechanisms in terms of hierarchical generative models approximating Bayesian inference. In other words, I examine whether the constrained mechanisms approach can be applied to the framework in which control mechanisms play an important explanatory role. I will argue that predictive processing models based on the free energy principle are amenable to this approach. In practice, this means that free energy principle offers a normative explanatory framework for predictive processing, and that in turn, this framework offers a biologically plausible account of the manner in which the principle is implemented in terms of hierarchical generative models and heterarchical active mechanisms. These analyzes are of great importance for those approaches that undermine the explanatory status of the free energy principle.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Piekarski, Michałm.piekarski@uksw.edu.pl0000-0002-9482-526X
Keywords: predictive processing; mechanisms; constraints; free energy principle; explanation; normativity.
Subjects: Specific Sciences > Cognitive Science > Action
Specific Sciences > Neuroscience > Cognitive Neuroscience
General Issues > Explanation
General Issues > Models and Idealization
General Issues > Philosophers of Science
Specific Sciences > Probability/Statistics
Specific Sciences > Physics > Statistical Mechanics/Thermodynamics
Depositing User: Dr Michał Piekarski
Date Deposited: 12 Feb 2022 22:44
Last Modified: 12 Feb 2022 22:44
Item ID: 20214
Subjects: Specific Sciences > Cognitive Science > Action
Specific Sciences > Neuroscience > Cognitive Neuroscience
General Issues > Explanation
General Issues > Models and Idealization
General Issues > Philosophers of Science
Specific Sciences > Probability/Statistics
Specific Sciences > Physics > Statistical Mechanics/Thermodynamics
Date: 9 January 2022
URI: http://philsci-archive.pitt.edu/id/eprint/20214

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