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The free energy principle made simpler but not too simple

Friston, K; Da Costa, L; Sajid, N; Heins, C; Ueltzhöffer, K; Pavliotis, GA; Parr, T; (2023) The free energy principle made simpler but not too simple. Physics Reports , 1024 pp. 1-29. 10.1016/j.physrep.2023.07.001. Green open access

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Abstract

This paper provides a concise description of the free energy principle, starting from a formulation of random dynamical systems in terms of a Langevin equation and ending with a Bayesian mechanics that can be read as a physics of sentience. It rehearses the key steps using standard results from statistical physics. These steps entail (i) establishing a particular partition of states based upon conditional independencies that inherit from sparsely coupled dynamics, (ii) unpacking the implications of this partition in terms of Bayesian inference and (iii) describing the paths of particular states with a variational principle of least action. Teleologically, the free energy principle offers a normative account of self-organisation in terms of optimal Bayesian design and decision-making, in the sense of maximising marginal likelihood or Bayesian model evidence. In summary, starting from a description of the world in terms of random dynamical systems, we end up with a description of self-organisation as sentient behaviour that can be interpreted as self-evidencing; namely, self-assembly, autopoiesis or active inference.

Type: Article
Title: The free energy principle made simpler but not too simple
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.physrep.2023.07.001
Publisher version: https://doi.org/10.1016/j.physrep.2023.07.001
Language: English
Additional information: © 2023 The Authors. Published by Elsevier B.V. under a Creative Commons license (http://creativecommons.org/licenses/by/4.0/).
Keywords: Self-organisation, Nonequilibrium, Variational inference, Bayesian, Markov blanket
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery.ucl.ac.uk/id/eprint/10175520
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