Natural selection for least action
Open accessAbstract
The second law of thermodynamics is a powerful imperative that has acquired several expressions during the past centuries. Connections between two of its most prominent forms, i.e. the evolutionary principle by natural selection and the principle of least action, are examined. Although no fundamentally new findings are provided, it is illuminating to see how the two principles rationalizing natural motions reconcile to one law. The second law, when written as a differential equation of motion, describes evolution along the steepest descents in energy and, when it is given in its integral form, the motion is pictured to take place along the shortest paths in energy. In general, evolution is a non-Euclidian energy density landscape in flattening motion.
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If workspace dynamics implement Bayesian model selection driven by minimization of free energy, then cognitive cycles may be fully isomorphic with both thermodynamic work cycles and selective pressures in generalized Darwinism.
“That is, if workspace dynamics implement Bayesian model selection—driven by the minimization of free energy—then cognitive cycles may be fully isomorphic with both thermodynamic work cycles (Kauffman and Clayton, 2006; Deacon, 2011) and selective pressures in the context of generalized Darwinism (Kaila and Annila, 2008; Campbell, 2016; Safron, 2019b).”
From An Integrated World Modeling Theory (IWMT) of Consciousness (2020) · cites this paper as Kaila and Annila, 2008
FEP-AI can be viewed as a Bayesian interpretation of generalized Darwinism, and so these nested couplings can also be viewed in terms of natural selection and niche construction unfolding over multiple hierarchical scales.
“It is important to remember that FEP-AI can be viewed as a Bayesian interpretation of generalized Darwinism (Kaila and Annila, 2008; Harper, 2011; Frank, 2012; Campbell, 2016), and so these nested couplings can also be viewed in terms of natural selection and niche construction unfolding over multiple hierarchical scales (Constant et al., 2018; Ramstead et al., 2018; Badcock et al., 2019).”
From An Integrated World Modeling Theory (IWMT) of Consciousness (2020) · cites this paper as Kaila and Annila, 2008
Cites
Natural process–Natural selection
Sharma, V., & Annila, A. (2007) · Biophysical Chemistry · doi:10.1016/j.bpc.2007.01.005 · Cited by 133 · see citing works
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Knowing one's place: a free-energy approach to pattern regulation
Friston, K., Levin, M., Sengupta, B., & Pezzulo, G. (2015) · Journal of The Royal Society Interface · doi:10.1098/rsif.2014.1383 · Cited by 234 · see citing works
Safron, A. (2020) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2020.00030 · Cited by 133 · see citing works
“It is important to remember that FEP-AI can be viewed as a Bayesian interpretation of generalized Darwinism (Kaila and Annila, 2008; Harper, 2011; Frank, 2012; Campbell, 2016), and so these nested couplings can also be viewed in terms of natural selection and niche construction unfolding over multiple hierarchical sca…”
BackgroundInfluentialModel averaging, optimal inference, and habit formation
FitzGerald, T. H. B., Dolan, R. J., & Friston, K. J. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00457 · Cited by 121 · see citing works
- Authors
- Kaila, V. R. I., & Annila, A.
- Affiliations
- University of Helsinki (FI)
- Corresponding author
- Annila, Arto
- Venue
- Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
- Publisher
- The Royal Society
- Published
- 2008-07-22
- Volume
- 464
- Issue
- 2099
- Pages
- 3055-3070
- ISSN
- 1364-5021 (ISSN-L)
- 1471-2946
- OpenAlex
- W2107914009
- Cited by
- 153
- References
- 1
- Citations by year
- 2026: 3 · 2025: 13 · 2024: 5 · 2023: 15 · 2022: 6 · 2021: 9 · 2020: 4 · 2019: 9 · 2018: 5 · 2017: 1 · 2016: 8 · 2015: 13 · 2014: 8 · 2013: 10 · 2012: 15
- FWCI
- 7.47
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences (publishedVersion, cc-by)
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Advanced Thermodynamics and Statistical Mechanics
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy and History of Science
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Systems and Dynamics
- Keywords
- natural selection, principle of least action, second law of thermodynamics, evolutionary principles, energy landscape, gradient descent, shortest path, differential equations of motion, non-Euclidean geometry
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