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Control flow in active inference systems Part I: Classical and quantum formulations of active inference

Fields, Chris; Fabrocini, Filippo; Friston, Karl; Glazebrook, James F; Hazan, Hananel; Levin, Michael; Marcianò, Antonino; (2023) Control flow in active inference systems Part I: Classical and quantum formulations of active inference. IEEE Transactions on Molecular, Biological, and Multi-Scale Communications 10.1109/TMBMC.2023.3272150. (In press). Green open access

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Abstract

Living systems face both environmental complexity and limited access to free-energy resources. Survival under these conditions requires a control system that can activate, or deploy, available perception and action resources in a context specific way. In this Part I, we introduce the free-energy principle (FEP) and the idea of active inference as Bayesian prediction-error minimization, and show how the control problem arises in active inference systems. We then review classical and quantum formulations of the FEP, with the former being the classical limit of the latter. In the accompanying Part II, we show that when systems are described as executing active inference driven by the FEP, their control flow systems can always be represented as tensor networks (TNs). We show how TNs as control systems can be implemented within the general framework of quantum topological neural networks, and discuss the implications of these results for modeling biological systems at multiple scales.

Type: Article
Title: Control flow in active inference systems Part I: Classical and quantum formulations of active inference
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TMBMC.2023.3272150
Publisher version: https://doi.org/10.1109/TMBMC.2023.3272150
Language: English
Additional information: This version is the author-accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions
Keywords: Control systems, Bayes methods, Behavioral sciences, Tensors, Switches, Probability distribution, Probabilistic logic
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/10171837
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