Some Interesting Observations on the Free Energy Principle

Biehl et al. (2021) present some interesting observations on an early formulation of the free energy principle. We use these observations to scaffold a discussion of the technical arguments that underwrite the free energy principle. This discussion focuses on solenoidal coupling between various (subsets of) states in sparsely coupled systems that possess a Markov blanket—and the distinction between exact and approximate Bayesian inference, implied by the ensuing Bayesian mechanics.

[1]  J. Bruineberg,et al.  The Emperor’s New Markov Blankets , 2020 .

[2]  Michael L. Anderson,et al.  The Markov blanket trick: On the scope of the free energy principle and active inference. , 2021, Physics of life reviews.

[3]  Grigorios A. Pavliotis,et al.  Bayesian mechanics for stationary processes , 2021, Proceedings of the Royal Society A.

[4]  Beren Millidge,et al.  How particular is the physics of the free energy principle? , 2021, Physics of life reviews.

[5]  R. Kanai,et al.  A Technical Critique of Some Parts of the Free Energy Principle , 2021, Entropy.

[6]  Ricardo Heras,et al.  Helmholtz’s theorem for two retarded fields and its application to Maxwell’s equations , 2020, European Journal of Physics.

[7]  Karl J. Friston,et al.  Neural Dynamics under Active Inference: Plausibility and Efficiency of Information Processing , 2020, Entropy.

[8]  Karl J. Friston,et al.  Natural selection finds natural gradient , 2020 .

[9]  Karl J. Friston,et al.  Active inference on discrete state-spaces: A synthesis , 2020, Journal of mathematical psychology.

[10]  R. Kanai,et al.  A technical critique of the free energy principle as presented in "Life as we know it" and related works , 2020, 2001.06408.

[11]  Karl J. Friston,et al.  Markov blankets, information geometry and stochastic thermodynamics , 2019, Philosophical Transactions of the Royal Society A.

[12]  Karl J. Friston.  A free energy principle for a particular physics , 2019, 1906.10184.

[13]  Karl J. Friston,et al.  The Anatomy of Inference: Generative Models and Brain Structure , 2018, Front. Comput. Neurosci..

[14]  M. Colombo,et al.  First principles in the life sciences: the free-energy principle, organicism, and mechanism , 2018, Synthese.

[15]  Eun-Jin Kim,et al.  Investigating Information Geometry in Classical and Quantum Systems through Information Length , 2018, Entropy.

[16]  Karl J. Friston,et al.  The Markov blankets of life: autonomy, active inference and the free energy principle , 2018, Journal of The Royal Society Interface.

[17]  Karl J. Friston,et al.  The graphical brain: Belief propagation and active inference , 2017, Network Neuroscience.

[18]  Karl J. Friston,et al.  Uncertainty, epistemics and active inference , 2017, Journal of The Royal Society Interface.

[19]  Andy Clark,et al.  How to Knit Your Own Markov Blanket , 2017 .

[20]  J. Hohwy.  The self-evidencing brain , 2016 .

[21]  Karl J. Friston,et al.  Active inference, communication and hermeneutics , 2015, Cortex.

[22]  A. Caticha.  The basics of information geometry , 2014, 1412.5633.

[23]  Karl J. Friston,et al.  Cognitive Dynamics: From Attractors to Active Inference , 2014, Proceedings of the IEEE.

[24]  Karl J. Friston.  Life as we know it , 2013, Journal of The Royal Society Interface.

[25]  F. Zhang,et al.  The potential and flux landscape theory of evolution. , 2012, The Journal of chemical physics.

[26]  U. Seifert.  Stochastic thermodynamics, fluctuation theorems and molecular machines , 2012, Reports on progress in physics. Physical Society.

[27]  Karl J. Friston,et al.  Free Energy, Value, and Attractors , 2011, Comput. Math. Methods Medicine.

[28]  P. Ao,et al.  Nonequilibrium steady state of a stochastic system driven by a nonlinear drift force. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[29]  P. Ao.  Emerging of Stochastic Dynamical Equalities and Steady State Thermodynamics from Darwinian Dynamics. , 2008, Communications in theoretical physics.

[30]  Gavin E Crooks,et al.  Measuring thermodynamic length. , 2007, Physical review letters.

[31]  T. Littenberg,et al.  Tests of Bayesian model selection techniques for gravitational wave astronomy , 2007, 0704.1808.

[32]  Karl J. Friston,et al.  Variational free energy and the Laplace approximation , 2007, NeuroImage.

[33]  Charles M. Bishop,et al.  Variational Message Passing , 2005, J. Mach. Learn. Res..

[34]  P. Ao,et al.  Laws in Darwinian Evolutionary Theory , 2005, ArXiv.

[35]  H. Qian,et al.  Thermodynamics of stoichiometric biochemical networks in living systems far from equilibrium. , 2005, Biophysical chemistry.

[36]  Shun-ichi Amari,et al.  Stochastic Reasoning, Free Energy, and Information Geometry , 2004, Neural Computation.

[37]  G. Buzsáki,et al.  Neuronal Oscillations in Cortical Networks , 2004, Science.

[38]  J. Fuster.  Upper processing stages of the perception–action cycle , 2004, Trends in Cognitive Sciences.

[39]  P Ao,et al.  LETTER TO THE EDITOR: Potential in stochastic differential equations: novel construction , 2004 .

[40]  P J Beek,et al.  Fokker-Planck perspective on stochastic delay systems: exact solutions and data analysis of biological systems. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[41]  Debra J. Searles,et al.  The Fluctuation Theorem , 2002 .

[42]  W. Fleming,et al.  Risk‐Sensitive Control and an Optimal Investment Model , 2000 .

[43]  N. Birbaumer,et al.  Electrocortical distinction of vocabulary types. , 1995, Electroencephalography and clinical neurophysiology.

[44]  D. Mackay.  Free energy minimisation algorithm for decoding and cryptanalysis , 1995 .

[45]  Richard Phillips Feynman,et al.  Statistical Mechanics: A Set of Lectures , 1972 .

[46]  Valerio Pascucci,et al.  The Helmholtz-Hodge Decomposition—A Survey , 2014 .

[47]  Matthew J. Beal.  Variational algorithms for approximate Bayesian inference , 2003 .

[48]  Judea Pearl,et al.  Graphical Models for Probabilistic and Causal Reasoning , 1997, The Computer Science and Engineering Handbook.

[49]  W Singer,et al.  Visual feature integration and the temporal correlation hypothesis. , 1995, Annual review of neuroscience.

[50]  R. Desimone,et al.  Attentional control of visual perception: cortical and subcortical mechanisms. , 1990, Cold Spring Harbor symposia on quantitative biology.

[51]  A. Tversky,et al.  Prospect theory: analysis of decision under risk , 1979 .