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Review
. 2018 Jan;15(138):20170792.
doi: 10.1098/rsif.2017.0792.

The Markov blankets of life: autonomy, active inference and the free energy principle

Michael Kirchhoff  1 , Thomas Parr  2 , Ensor Palacios  3 , Karl Friston  4 , Julian Kiverstein  5
Affiliations
Review

The Markov blankets of life: autonomy, active inference and the free energy principle

Michael Kirchhoff et al. J R Soc Interface. 2018 Jan.

Abstract

This work addresses the autonomous organization of biological systems. It does so by considering the boundaries of biological systems, from individual cells to Home sapiens, in terms of the presence of Markov blankets under the active inference scheme-a corollary of the free energy principle. A Markov blanket defines the boundaries of a system in a statistical sense. Here we consider how a collective of Markov blankets can self-assemble into a global system that itself has a Markov blanket; thereby providing an illustration of how autonomous systems can be understood as having layers of nested and self-sustaining boundaries. This allows us to show that: (i) any living system is a Markov blanketed system and (ii) the boundaries of such systems need not be co-extensive with the biophysical boundaries of a living organism. In other words, autonomous systems are hierarchically composed of Markov blankets of Markov blankets-all the way down to individual cells, all the way up to you and me, and all the way out to include elements of the local environment.

Keywords: Markov blanket; active inference; autonomy; ensemble Markov blanket; free energy principle.

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Conflict of interest statement

We have no disclosures or conflict of interest.

Figures

Figure 1.
Figure 1.
A schematic depiction of a Markov blanket with full conditionals.
Figure 2.
Figure 2.
Two oscillating (i.e. coupled random dynamical) systems, A and B, suspended from a beam that is itself able to move. The two arrows illustrate the coupling between pendulum A and pendulum B (for additional discussion, see [16]).
Figure 3.
Figure 3.
Nested Markov blankets of Markov blankets at different levels of organization.
Figure 4.
Figure 4.
Markov blankets of Markov blankets. This illustrates how the conditional dependency structure of Markov blankets can be replicated at larger spatial scales. Internal (red) states are separated from external (blue) states via sensory (yellow) states and active (orange) states at different scales of organization [46].
Figure 5.
Figure 5.
Illustration of Jensen's inequality used to show that the free energy is an upper bound on surprise.
See this image and copyright information in PMC

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