Hostname: page-component-78c5997874-dh8gc Total loading time: 0 Render date: 2024-11-10T17:27:11.888Z Has data issue: false hasContentIssue false

Making reification concrete: A response to Bruineberg et al.

Published online by Cambridge University Press:  29 September 2022

Mel Andrews*
Affiliation:
Department of Philosophy, The University of Cincinnati, Cincinnati, OH 45221, USA mel.andrews@tufts.edu www.mel-andrews.com

Abstract

The principal target of this article is the reification Bruineberg et al. perceive of formalism within the literature on the variational free energy minimization (VFEM) framework. The authors do not provide a definition of reification, as none yet exists. Here I offer one. On this definition, the objects of the authors' critiques fall short of full-blown reification – as do the authors themselves.

Type
Open Peer Commentary
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Andrews, M. (2021). The math is not the territory: Navigating the free energy principle. Biology & Philosophy, 36(3), 119.CrossRefGoogle Scholar
Kirchhoff, M., Parr, T., Palacios, E., Friston, K., & Kiverstein, J. (2018). The Markov blankets of life: Autonomy, active inference and the free energy principle. Journal of the Royal Society Interface, 15(138), 20170792.CrossRefGoogle ScholarPubMed
Kuchling, F., Friston, K., Georgiev, G., & Levin, M. (2019). Morphogenesis as Bayesian inference: A variational approach to pattern formation and control in complex biological systems. Physics of Life Reviews, 33, 88108.CrossRefGoogle ScholarPubMed
Nguyen, J., & Frigg, R. (2021). Mathematics is not the only language in the book of nature. Synthese, 198(24), 59415962.CrossRefGoogle Scholar
Pearl, J. (1988). Probabilistic reasoning in intelligent systems: Networks of plausible inference. Morgan Kaufmann.Google Scholar
Potochnik, A. (2017). Idealization and the aims of science. University of Chicago Press.CrossRefGoogle Scholar
Rubin, S., Parr, T., Da Costa, L., & Friston, K. (2020). Future climates: Markov blankets and active inference in the biosphere. Journal of the Royal Society Interface, 17(172), 20200503.CrossRefGoogle ScholarPubMed
Weisberg, M. (2013). Simulation and similarity: Using models to understand the world. Oxford University Press.CrossRefGoogle Scholar