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A tale of two densities: Active inference is enactive inference

Ramstead, Maxwell J. D. and Kirchhoff, Michael D. and Friston, Karl J. (2019) A tale of two densities: Active inference is enactive inference. [Preprint]

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Abstract

The aim of this paper is to clarify how best to interpret some of the central constructs that underwrite the free-energy principle (FEP) – and its corollary, active inference – in theoretical neuroscience and biology: namely, the role that generative models and variational densities play in this theory. We argue that these constructs have been systematically misrepresented in the literature; because of the conflation between the FEP and active inference, on the one hand, and distinct (albeit closely related) Bayesian formulations, centred on the brain – variously known as predictive processing, predictive coding, or the prediction error minimisation framework. More specifically, we examine two contrasting interpretations of these models: a structural representationalist interpretation and an enactive interpretation. We argue that the structural representationalist interpretation of generative and recognition models does not do justice to the role that these constructs play in active inference under the FEP. We propose an enactive interpretation of active inference – what might be called enactive inference. In active inference under the FEP, the generative and recognition models are best cast as realising inference and control – the self-organising, belief-guided selection of action policies – and do not have the properties ascribed by structural representationalists.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Ramstead, Maxwell J. D.maxwell.d.ramstead@gmail.com0000-0002-1477-8177
Kirchhoff, Michael D.
Friston, Karl J.k.friston@ucl.ac.uk
Keywords: Active inference; Free-energy principle; Representationalism; Enactivism; Structural representations
Subjects: Specific Sciences > Cognitive Science > Action
Specific Sciences > Biology
General Issues > Causation
Specific Sciences > Neuroscience > Cognitive Neuroscience
Specific Sciences > Cognitive Science
Specific Sciences > Cognitive Science > Computation
Specific Sciences > Artificial Intelligence
General Issues > Explanation
General Issues > Models and Idealization
Specific Sciences > Cognitive Science > Perception
Specific Sciences > Probability/Statistics
Specific Sciences > Physics > Statistical Mechanics/Thermodynamics
Specific Sciences > Neuroscience > Systems Neuroscience
Depositing User: Mr MJD R
Date Deposited: 01 Jul 2019 18:31
Last Modified: 01 Jul 2019 18:31
Item ID: 16167
Subjects: Specific Sciences > Cognitive Science > Action
Specific Sciences > Biology
General Issues > Causation
Specific Sciences > Neuroscience > Cognitive Neuroscience
Specific Sciences > Cognitive Science
Specific Sciences > Cognitive Science > Computation
Specific Sciences > Artificial Intelligence
General Issues > Explanation
General Issues > Models and Idealization
Specific Sciences > Cognitive Science > Perception
Specific Sciences > Probability/Statistics
Specific Sciences > Physics > Statistical Mechanics/Thermodynamics
Specific Sciences > Neuroscience > Systems Neuroscience
Date: 2019
URI: https://philsci-archive.pitt.edu/id/eprint/16167

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