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Get Free AccessThis paper introduces a variational formulation of natural selection, paying special attention to the nature of "things" and the way that different "kinds" of "things" are individuated from - and influence - each other. We use the Bayesian mechanics of particular partitions to understand how slow phylogenetic processes constrain - and are constrained by - fast, phenotypic processes. The main result is a formulation of adaptive fitness as a path integral of phenotypic fitness. Paths of least action, at the phenotypic and phylogenetic scales, can then be read as inference and learning processes, respectively. In this view, a phenotype actively infers the state of its econiche under a generative model, whose parameters are learned via natural (bayesian model selection). The ensuing variational synthesis features some unexpected aspects. Perhaps the most notable is that it is not possible to describe or model a population of conspecifics per se. Rather, it is necessary to consider populations - and nested meta-populations - of different natural kinds that influence each other. This paper is limited to a description of the mathematical apparatus and accompanying ideas. Subsequent work will use these methods for simulations and numerical analyses - and identify points of contact with related mathematical formulations of evolution.
Karl Friston, Daniel Friedman, Axel Constant, V. Bleu Knight, Thomas Parr, John O. Campbell (2023). A variational synthesis of evolutionary and developmental dynamics. , DOI: https://doi.org/10.48550/arxiv.2303.04898.
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Type
Preprint
Year
2023
Authors
6
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.48550/arxiv.2303.04898
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