The Active Inference Approach to Ecological Perception: General Information Dynamics for Natural and Artificial Embodied Cognition

Adam Linson, Andrew Clark, Subramanian Ramamoorthy, Karl Friston

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
Article number21
Number of pages21
JournalFrontiers in Robotics and AI
Volume5
Early online date8 Mar 2018
DOIs
Publication statusPublished - 8 Mar 2018

Keywords / Materials (for Non-textual outputs)

  • free energy
  • uncertainty
  • self-organization
  • embodiment
  • evolution
  • affordances
  • skilled expertise
  • frame problem

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