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Evolution of Social Learning with Payoff and Content Bias

Author

Listed:
  • Charles Perreault

    (Institute of Human Origins, School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 874102, USA)

  • Robert Boyd

    (Institute of Human Origins, School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 874102, USA)

Abstract

There has been much theoretical work aimed at understanding the evolution of social learning; and in most of it, individual and social learning are treated as distinct processes. A number of authors have argued that this approach is faulty because the same psychological mechanisms underpin social and individual learning. In previous work, we analyzed a simple model in which both individual and social learning are the result of a single learning process. Here, we extend this approach by showing how payoff and content biases evolve. We show that payoff bias leads to higher average fitness when environments are noisy and change rapidly. Content bias always evolves when the expected fitness benefits of alternative traits differ.

Suggested Citation

  • Charles Perreault & Robert Boyd, 2021. "Evolution of Social Learning with Payoff and Content Bias," Games, MDPI, vol. 13(1), pages 1-15, December.
  • Handle: RePEc:gam:jgames:v:13:y:2021:i:1:p:7-:d:712471
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    References listed on IDEAS

    as
    1. Schlag, Karl H., 1998. "Why Imitate, and If So, How?, : A Boundedly Rational Approach to Multi-armed Bandits," Journal of Economic Theory, Elsevier, vol. 78(1), pages 130-156, January.
    2. Schlag, Karl H., 1998. "Why Imitate, and If So, How?, : A Boundedly Rational Approach to Multi-armed Bandits," Journal of Economic Theory, Elsevier, vol. 78(1), pages 130-156, January.
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