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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.
|Number of pages||21|
|Journal||Frontiers in Robotics and AI|
|Early online date||8 Mar 2018|
|Publication status||Published - 8 Mar 2018|
- free energy
- skilled expertise
- frame problem
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- 1 Finished
XSPECT: Expecting Ourselves: Embodied Prediction and the Construction of Conscious Experience
Clark, A. & Podhortzer Carmel, D.
1/01/17 → 30/09/21