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Abstract
This paper presents a heuristic proof (and simulations of a primordial soup) suggesting that life—or biological self-organization—is an inevitable and emergent property of any (ergodic) random dynamical system that possesses a Markov blanket. This conclusion is based on the following arguments: if the coupling among an ensemble of dynamical systems is mediated by short-range forces, then the states of remote systems must be conditionally independent. These independencies induce a Markov blanket that separates internal and external states in a statistical sense. The existence of a Markov blanket means that internal states will appear to minimize a free energy functional of the states of their Markov blanket. Crucially, this is the same quantity that is optimized in Bayesian inference. Therefore, the internal states (and their blanket) will appear to engage in active Bayesian inference. In other words, they will appear to model—and act on—their world to preserve their functional and structural integrity, leading to homoeostasis and a simple form of autopoiesis.
Highlights
How can the events in space and time which take place within the spatial boundary of a living organism be accounted for by physics and chemistry?Erwin Schrodinger [1, p. 2]The emergence of life—or biological self-organization—is an intriguing issue that has been addressed in many guises in the biological and physical sciences [1,2,3,4,5]
This paper suggests that biological self-organization is not as remarkable as one might think—and is inevitable, given local interactions between the states of coupled dynamical systems
The treatment offered in this paper is rather abstract and restricts itself to some basic observations about how coupled dynamical systems organize themselves over time
Summary
How can the events in space and time which take place within the spatial boundary of a living organism be accounted for by physics and chemistry?. The long-term average of surprise is entropy This means that minimizing free energy—through selectively sampling sensory input—places an upper bound on the entropy or dispersion of sensory states. Biological systems act on the world to place an upper bound on the dispersion of their sensed states, while using those sensations to infer external states of the world This inference makes the free energy bound a better approximation to the surprise that action is trying to minimize [21]. This paper resolves the somewhat tautological aspect of this argument by turning it around to suggest: any system that exists will appear to minimize free energy and engage in active inference This apparently inferential or mindful behaviour is (almost) inevitable. This proof of principle rests on four attributes of—or tests for—self-organization that may themselves have interesting implications
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