ArticleRoyal Society open science2019
Multilevel selection as Bayesian inference, major transitions in individuality as structure learning.
Article in Royal Society open science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- The selfish ribosome.PLoS biology · 2026Article
- The selfish ribosome.ArXiv · 2026Article
- Toward a theory of evolution as multilevel learning.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Thermodynamics of evolution and the origin of life.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Novelty and imitation within the brain: a Darwinian neurodynamic approach to combinatorial problems.Scientific reports · 2021Article
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3 authors.
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Abstract
Complexity of life forms on the Earth has increased tremendously, primarily driven by subsequent evolutionary transitions in individuality, a mechanism in which units formerly being capable of independent replication combine to form higher-level evolutionary units. Although this process has been likened to the recursive combination of pre-adapted sub-solutions in the framework of learning theory, no general mathematical formalization of this analogy has been provided yet. Here we show, building on former results connecting replicator dynamics and Bayesian update, that (i) evolution of a hierarchical population under multilevel selection is equivalent to Bayesian inference in hierarchical Bayesian models and (ii) evolutionary transitions in individuality, driven by synergistic fitness interactions, is equivalent to learning the structure of hierarchical models via Bayesian model comparison. These correspondences support a learning theory-oriented narrative of evolutionary complexification: the complexity and depth of the hierarchical structure of individuality mirror the amount and complexity of data that have been integrated about the environment through the course of evolutionary history.
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