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Embracing sensorimotor history: Time-synchronous and time-unrolled Markov blankets in the free-energy principle

Published online by Cambridge University Press:  29 September 2022

Nathaniel Virgo ,
Fernando E. Rosas Open the ORCID record for Fernando E. Rosas [Opens in a new window]  and
Martin Biehl
Nathaniel Virgo
Affiliation:
Earth-Life Science Institute (ELSI), Tokyo Institute of Technology, Tokyo 152-8550, Japan nathanielvirgo@elsi.jp http://www.elsi.jp/en/members/researchers/nvirgo
Fernando E. Rosas
Affiliation:
Department of Brain Science, Centre for Psychedelic Research, Imperial College London, London W12 0NN, UK f.rosas@imperial.ac.uk https://www.imperial.ac.uk/people/f.rosas Data Science Institute, Imperial College London, London W7 2AZ, UK Centre for Complexity Science, Imperial College London, London W7 2AZ, UK Department of Informatics, University of Sussex, Brighton BN1 9QJ, UK
Martin Biehl
Affiliation:
Cross Labs, Cross Compass, Tokyo 104-0045, Japan martin.biehl@cross-compass.com https://twitter.com/36zimmer
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Abstract

The free-energy principle (FEP) builds on an assumption that sensor–motor loops exhibit Markov blankets in stationary state. We argue that there is rarely reason to assume a system's internal and external states are conditionally independent given the sensorimotor states, and often reason to assume otherwise. However, under mild assumptions internal and external states are conditionally independent given the sensorimotor history.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 45 , 2022 , e215
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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References

Aguilera, M., Millidge, B., Tschantz, A., & Buckley, C. L. (2021). How particular is the physics of the free energy principle? Physics of Life Reviews, 40, 24–40.CrossRefGoogle ScholarPubMed
Biehl, M., Pollock, F. A., & Kanai, R. (2021). A technical critique of some parts of the free energy principle. Entropy, 23(3), 293.CrossRefGoogle ScholarPubMed
Cover, T. M., & Thomas, J. A. (2006). Elements of information theory (2nd ed.). Wiley.Google Scholar
Friston, K., Heins, C., Ueltzhöffer, K., Da Costa, L., & Parr, T. (2021a). Stochastic chaos and Markov blankets. Entropy, 23(9), 1220.CrossRefGoogle Scholar
Friston, K. J., Da Costa, L., & Parr, T. (2021b). Some interesting observations on the free energy principle. Entropy, 23(8), 1076.CrossRefGoogle Scholar
Parr, T., Da Costa, L., Heins, C., Ramstead, M. J. D., & Friston, K. J. (2021). Memory and Markov blankets. Entropy, 23(9), 1105.CrossRefGoogle ScholarPubMed
Pearl, J. (1988). Probabilistic reasoning in intelligent systems: Networks of plausible inference. Morgan Kaufmann.Google Scholar
Rosas, F. E., Mediano, P. A., Biehl, M., Chandaria, S., & Polani, D. (2020). Causal blankets: Theory and algorithmic framework. In Verbelen, T., Lanillos, P., Buckley, C. L., & De Boom, C. (Eds.), International workshop on active inference (pp. 187–198). Springer.CrossRefGoogle Scholar