Markov Blanket

#concept1 mention

If we want to Prioritise abstraction over metaphor, the concept of a System Boundary needs to be stripped of its metaphorical content. The concept of a Markov blanket delivers exactly that:

[T]]he notion of a Markov blanket allows one to define any System or structure in a way that distinguishes it from the Environment or milieu in which it resides. The Markov blanket plays the role of a statistical boundary that allows one to talk about a system per se.

The concept has been developed in statistics and machine learning, where

when one wants to infer a random variable with a set of variables, usually a subset is enough, and other variables are useless. Such a subset that contains all the useful information is called a Markov blanket.Wikipedia

As these variables represent specific features or states of systems, we can transpose this into the following:

A Markov blanket is a set of states that separates the internal or intrinsic states of a structure from extrinsic or external states. Importantly, when interactions between states are spatially dependent, as is the case for states pertaining to the physical description of biological organisms, this separation can be spatial in nature. Consequently, in this setting, a Markov blanket describes a spatial boundary.Palacios et al. (2020), 1

These states that “encapsulate” the system’s internal states can also be called boundary states.

Because The world is a hierarchy of systems, we can describe it as being structured by “Markov blankets all the way down”Friston (2019), 7

.

If we “carve up” reality at system boundaries, and these boundaries are objectively defined as Markov blankets, this carving up has an ontological character – it is about systems themselves, not just Models of them. This is a stronger claim than the one that systems are epistemologically defined “real patterns”.Dennett (1991). Cf. Causal Emergence for more on this. The ontological character allows us to objectively identify Missing Systems.

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