Particular flows and attracting sets: A comment on "How particular is the physics of the free energy principle?" by Aguilera, Millidge, Tschantz and Buckley.

@article{Heins2022ParticularFA,
  title={Particular flows and attracting sets: A comment on "How particular is the physics of the free energy principle?" by Aguilera, Millidge, Tschantz and Buckley.},
  author={Conor Heins},
  journal={Physics of life reviews},
  year={2022},
  volume={42},
  pages={
          43-48
        }
}
  • Conor Heins
  • Published 19 May 2022
  • Physics
  • Physics of life reviews

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SHOWING 1-10 OF 15 REFERENCES
How particular is the physics of the free energy principle?
A Technical Critique of Some Parts of the Free Energy Principle
TLDR
It is proved by counterexamples that the original free energy lemma, when taken at face value, is wrong and it is concluded that the interpretation in terms of Bayesian inference hinges on this point, and is not sufficiently justified.
Markov blankets, information geometry and stochastic thermodynamics
TLDR
There is a natural Bayesian mechanics for any system that possesses a Markov blanket, which means that there is an explicit link between the inference performed by internal states and their energetics—as characterized by their stochastic thermodynamics.
The free energy principle made simpler but not too simple
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
Stochastic Chaos and Markov Blankets
TLDR
This treatment of random dynamical systems considers the existence—and identification— of conditional independencies at nonequilibrium steady-state, and shows how Markov blankets can be identified to characterise the coupling between internal and external states in terms of a generalised synchrony or synchronisation of chaos.
A free energy principle for a particular physics
TLDR
The main contribution is to examine the implications of Markov blankets for self-organisation to nonequilibrium steady-state and recover an information geometry and accompanying free energy principle that allows one to interpret the internal states of something as representing or making inferences about its external states.
Characterising the nonequilibrium stationary states of Ornstein–Uhlenbeck processes
We characterise the nonequilibrium stationary state of a generic multivariate Ornstein–Uhlenbeck process involving degrees of freedom. The irreversibility of the process is encoded in the
Some Interesting Observations on the Free Energy Principle
TLDR
This discussion focuses on solenoidal coupling between various 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.
Bayesian mechanics for stationary processes
TLDR
It follows that active states can be seen as performing active inference and well-known forms of stochastic control, which are prominent formulations of adaptive behaviour in theoretical biology and engineering.
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