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Free Energy: A User's Guide

Mann, Stephen Francis and Pain, Ross and Kirchhoff, Michael (2021) Free Energy: A User's Guide. [Preprint]

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Abstract

Over the last fifteen years, an ambitious explanatory framework has been proposed to unify explanations across biology and cognitive science. Active inference, whose most famous tenet is the free energy principle, has inspired excitement and confusion in equal measure. Here, we lay the ground for proper critical analysis of active inference, in three ways. First, we give simplified versions of its core mathematical models. Second, we outline the historical development of active inference and its relationship to other theoretical approaches. Third, we describe three different kinds of claim -- labelled mathematical, empirical and general -- routinely made by proponents of the framework, and suggest dialectical links between them. Overall, we aim to increase philosophical understanding of active inference so that it may be more readily evaluated.

This is a manuscript draft of the Introduction to the Topical Collection "The Free Energy Principle: From Biology to Cognition", forthcoming in Biology & Philosophy.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Mann, Stephen Francisstephenfmann@gmail.com0000-0002-4136-8595
Pain, Rossross.pain@anu.edu.au0000-0002-5354-6301
Kirchhoff, Michaelkirchhof@uow.edu.au0000-0002-2530-0718
Additional Information: Introduction to the Biology & Philosophy Topical Collection "The Free Energy Principle: From Biology to Cognition". Comments and suggestions welcome!
Keywords: free energy principle; active inference; models; computational cognitive science
Subjects: Specific Sciences > Biology
Specific Sciences > Neuroscience > Cognitive Neuroscience
General Issues > Decision Theory
General Issues > Explanation
General Issues > Models and Idealization
Specific Sciences > Probability/Statistics
Depositing User: Dr Stephen Francis Mann
Date Deposited: 12 Dec 2021 01:07
Last Modified: 12 Dec 2021 01:07
Item ID: 19961
Subjects: Specific Sciences > Biology
Specific Sciences > Neuroscience > Cognitive Neuroscience
General Issues > Decision Theory
General Issues > Explanation
General Issues > Models and Idealization
Specific Sciences > Probability/Statistics
Date: 6 December 2021
URI: http://philsci-archive.pitt.edu/id/eprint/19961

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