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Universal Darwinism As a Process of Bayesian Inference.

John O Campbell1

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Frontiers in Systems Neuroscience
|July 5, 2016
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Natural selection is a form of Bayesian inference, challenging the view that this process is exclusive to human cognition. Free energy minimization unifies natural selection and universal Darwinism under a single mathematical framework.

Keywords:
Bayesian inferenceUniversal Darwinismfree energyinformationnatural selection

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Area of Science:

  • Evolutionary Biology
  • Theoretical Biology
  • Cognitive Science

Background:

  • Mathematical frameworks of natural selection align with Bayesian updating.
  • Bayesian inference is often restricted to human mental processes.

Purpose of the Study:

  • To demonstrate natural selection as a process of Bayesian inference.
  • To present free energy minimization as a unifying framework for universal Darwinism.

Main Methods:

  • Equivalence of natural selection frameworks to Bayes' Theorem.
  • Casting Bayesian inference in terms of free energy minimization.
  • Analyzing natural selection as a generative model and experimental outcome.

Main Results:

  • Natural selection functions as Bayesian inference, updating generative models via 'surprise'.
  • This process aligns with generalized Darwinian mechanisms (Dawkins, Campbell).
  • Bayesian inference is identified as a core algorithm in various evolutionary processes.

Conclusions:

  • Natural selection provides a counterexample to the human-centric view of Bayesian inference.
  • Free energy minimization offers a unifying mathematical principle for universal Darwinism.
  • This framework encompasses natural selection, mental model evolution, and cultural evolution.