Abstract

The emerging neurocomputational vision of humans as embodied, ecologically embedded, social agents—who shape and are shaped by their environment—offers a golden opportunity to revisit and revise ideas about the physical and information-theoretic underpinnings of life, mind, and consciousness itself. In particular, the active inference framework (AIF) makes it possible to bridge connections from computational neuroscience and robotics/AI to ecological psychology and phenomenology, revealing common underpinnings and overcoming key limitations. AIF opposes the mechanistic to the reductive, while staying fully grounded in a naturalistic and information-theoretic foundation, using the principle of free energy minimization. The latter provides a theoretical basis for a unified treatment of particles, organisms, and interactive machines, spanning from the inorganic to organic, non-life to life, and natural to artificial agents. We provide a brief introduction to AIF, then explore its implications for evolutionary theory, ecological psychology, embodied phenomenology, and robotics/AI research. We conclude the paper by considering implications for machine consciousness.

Highlights

  • Reviewed by: Tony Belpaeme, Plymouth University, United Kingdom Owen E

  • We provide a brief introduction to active inference framework (AIF), explore its implications for evolutionary theory, ecological psychology, embodied phenomenology, and robotics/AI research

  • Subsequent sections unpack the framework in greater detail, drawing out its implications for evolutionary theory, ecological psychology, embodied

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Summary

Setting Up the Framework

AIF considers a thermodynamically open, embodied, and environmentally embedded agent (see, e.g., Friston, 2009, 2010; Friston et al, 2010, 2015a,b, 2016, 2017a,b,c). Taking a broad bio-evolutionary view, AIF regards the entire embodied agent as a generative model of the organism-relevant thermodynamics of its ecological niche (see below), in that the agent is a member of a phylogenetic species that is co-stabilized with its niche. This notion encompasses the reciprocal organism/niche coevolutionary relationship (Laland et al, 2017). Even when discussing PP—the human (neuronal) instantiation of active inference—the brain should be understood as “taking a back seat” to the body, serving the body by facilitating more complex coordination Such coordination, including the dramatic niche reshaping seen in human culture, serves to co-stabilize organism and niche. Such brainless organisms should be kept in mind whenever we “skip ahead” to the AIF description of human neural architecture—and its role in navigating the complexity of our cultural niche.

Generative Model Basics
Further Preliminaries
DEMYSTIFYING FEM
Design Requirements for a Brain
EVOLUTION THROUGH A CYBERNETIC LENS
Self-Organization and System Boundaries
Ecological Context
Complexity and Spatiotemporal Integration
The Poverty of Indirect and Direct Perception
GIBSON RECONFIGURED
Initial Mappings
Affordances and Policies
SKATING UNCERTAINTY
Generalized Affordance Theory
Skilled Expertise
The Frame Problem
SELF-REFLECTIVE EPISTEMIC FORAGING
CONCLUSION
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