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Bayesian mechanics for stationary processes

Da Costa, L; Friston, K; Heins, C; Pavliotis, GA; (2021) Bayesian mechanics for stationary processes. PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES , 477 (2256) , Article 20210518. 10.1098/rspa.2021.0518. Green open access

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Abstract

This paper develops a Bayesian mechanics for adaptive systems. Firstly, we model the interface between a system and its environment with a Markov blanket. This affords conditions under which states internal to the blanket encode information about external states. Second, we introduce dynamics and represent adaptive systems as Markov blankets at steady state. This allows us to identify a wide class of systems whose internal states appear to infer external states, consistent with variational inference in Bayesian statistics and theoretical neuroscience. Finally, we partition the blanket into sensory and active states. It follows that active states can be seen as performing active inference and well-known forms of stochastic control (such as PID control), which are prominent formulations of adaptive behaviour in theoretical biology and engineering.

Type: Article
Title: Bayesian mechanics for stationary processes
Open access status: An open access version is available from UCL Discovery
DOI: 10.1098/rspa.2021.0518
Publisher version: https://doi.org/10.1098/rspa.2021.0518
Language: English
Additional information: © 2021 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/ by/4.0/, which permits unrestricted use, provided the original author and source are credited.
Keywords: Science & Technology, Multidisciplinary Sciences, Science & Technology - Other Topics, Markov blanket, variational Bayesian inference, active inference, non-equilibrium steady state, predictive processing, free-energy principle, FREE-ENERGY PRINCIPLE, ENTROPY PRODUCTION, INFERENCE, BRAIN, MODEL
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/10140904
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