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We summarize the original formulation of the free energy principle, and highlight some technical issues. We discuss how these issues affect related results involving generalised coordinates and, where appropriate, mention consequences for…

Neurons and Cognition · Quantitative Biology 2021-03-02 Martin Biehl , Felix A. Pollock , Ryota Kanai

In this commentary, we respond to a technical analysis of the Free Energy Principle (hereafter: FEP) presented in "How particular is the physics of the Free Energy Principle" by Aguilera et al. In the target article, the authors analyzed…

Statistical Mechanics · Physics 2022-07-13 Conor Heins , Lancelot Da Costa

The free energy principle (FEP) states that any dynamical system can be interpreted as performing Bayesian inference upon its surrounding environment. In this work, we examine in depth the assumptions required to derive the FEP in the…

Neurons and Cognition · Quantitative Biology 2022-05-23 Miguel Aguilera , Beren Millidge , Alexander Tschantz , Christopher L. Buckley

This monograph attempts a theory of every 'thing' that can be distinguished from other things in a statistical sense. The ensuing statistical independencies, mediated by Markov blankets, speak to a recursive composition of ensembles (of…

Neurons and Cognition · Quantitative Biology 2019-06-26 Karl Friston

This paper presents a continuous, information-theoretic extension of the Free Energy Principle through the concept of Markov blanket density, i.e., a scalar field that quantifies the degree of conditional independence between internal and…

Neurons and Cognition · Quantitative Biology 2025-08-12 Luca M. Possati

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.…

In this comment on "The Markov blanket trick: On the scope of the free energy principle and active inference" by Raja and colleagues (2021) in Physics of Life Reviews, I argue that the argument presented by the authors is valid; however, I…

Neurons and Cognition · Quantitative Biology 2022-11-30 Maxwell J. D Ramstead

The free energy principle has been proposed as a unifying account of brain function. It is closely related, and in some cases subsumes, earlier unifying ideas such as Bayesian inference, predictive coding, and active learning. This article…

Neurons and Cognition · Quantitative Biology 2022-11-30 Samuel J. Gershman

In this commentary, I expand on the analysis of the recent article "How particular is the physics of the Free Energy Principle?" by Aguilera et al. by studying the flow fields of linear diffusions, and particularly the rotation of their…

Neurons and Cognition · Quantitative Biology 2022-07-20 Conor Heins

The Free-Energy Principle (FEP) [1-3] has been adopted in a variety of ambitious proposals that aim to characterize all adaptive, sentient, and cognitive systems within a unifying framework. Judging by the amount of attention it has…

Neurons and Cognition · Quantitative Biology 2024-01-18 Zahra Sheikhbahaee , Adam Safron , Casper Hesp , Guillaume Dumas

In their target paper, Bruineberg and colleagues provide us with a timely opportunity to discuss the formal constructs and philosophical implications of the free-energy principle. I critically discuss their proposed distinction between…

Neurons and Cognition · Quantitative Biology 2022-01-05 Maxwell J. D. Ramstead

In this PhD thesis, we explore and apply methods inspired by the free energy principle to two important areas in machine learning and neuroscience. The free energy principle is a general mathematical theory of the necessary…

Artificial Intelligence · Computer Science 2021-08-31 Beren Millidge

The concept of free energy has its origins in 19th century thermodynamics, but has recently found its way into the behavioral and neural sciences, where it has been promoted for its wide applicability and has even been suggested as a…

Neurons and Cognition · Quantitative Biology 2020-12-08 Sebastian Gottwald , Daniel A. Braun

In a recent technical critique of the free energy principle (FEP) due to Aguilera-Millidge-Tschantz-Buckley, it is argued that there are a number of instances where the FEP$\unicode{x2014}$as conventionally written, in terms of densities…

Statistical Mechanics · Physics 2022-06-02 Dalton A R Sakthivadivel

In this paper, a simple case of Bayesian mechanics under the free energy principle is formulated in axiomatic terms. We argue that any dynamical system with constraints on its dynamics necessarily looks as though it is performing inference…

Mathematical Physics · Physics 2022-04-27 Dalton A R Sakthivadivel

The Free Energy Principle (FEP) states that under suitable conditions of weak coupling, random dynamical systems with sufficient degrees of freedom will behave so as to minimize an upper bound, formalized as a variational free energy, on…

Quantum Physics · Physics 2022-07-21 Chris Fields , Karl Friston , James F. Glazebrook , Michael Levin

Wright and Bourkes compelling article rightly points out that existing models of embryogenesis fail to explain the mechanisms and functional significance of the dynamic connections among neurons. We pursue their account of Dynamic Logic by…

Neurons and Cognition · Quantitative Biology 2020-07-31 Ines Hipolito , Maxwell Ramstead , Axel Constant , Karl Friston

This thesis focuses on three fundamental aspects of biological systems; namely, entropy production, Bayesian mechanics, and the free-energy principle. The contributions are threefold: 1) We compute the entropy production for a greater class…

Mathematical Physics · Physics 2024-10-16 Lancelot Da Costa

The aim of this paper is to introduce a field of study that has emerged over the last decade called Bayesian mechanics. Bayesian mechanics is a probabilistic mechanics, comprising tools that enable us to model systems endowed with a…

The Free-Energy-Principle (FEP) is an influential and controversial theory which postulates a deep and powerful connection between the stochastic thermodynamics of self-organization and learning through variational inference. Specifically,…

Artificial Intelligence · Computer Science 2021-10-05 Beren Millidge , Anil Seth , Christopher L Buckley
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