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Eita Nakamura1

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Statistical learning shapes cultural evolution by influencing trait transmission. Our study shows conjugate distributions emerge from this process, impacting cultural trait distribution in populations.

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Area of Science:

  • Evolutionary Psychology
  • Cultural Evolution
  • Cognitive Science

Background:

  • Intelligent behaviors and cultural traits are often transmitted via statistical learning.
  • Understanding the mechanisms of cultural transmission is key to explaining cultural evolution.

Purpose of the Study:

  • To investigate the impact of statistical learning on cultural evolution.
  • To determine if statistical learning leads to predictable distributions of cultural traits.
  • To model the emergence of cultural trait distributions.

Main Methods:

  • Large-scale analysis of musical data to identify statistical properties of cultural products.
  • Development of a mathematical model of cultural evolution that incorporates statistical learning.
  • Analytical derivation of equilibrium distributions within the model.

Main Results:

  • Statistical parameters of musical products approximate beta and other conjugate distributions.
  • Conjugate distributions emerge at equilibrium in models with statistical learning and oblique transmission.
  • The distribution of a cultural trait is influenced by individual production models governed by conjugate distribution laws.

Conclusions:

  • Statistical learning is a significant driver of cultural evolution, leading to predictable trait distributions.
  • Conjugate distributions represent a fundamental outcome of cultural transmission via statistical learning.
  • Findings open avenues for theoretical and experimental research in cultural evolution and social learning.