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Success-biased social learning: Cultural and evolutionary dynamics

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  • Baldini, Ryan

Abstract

Success bias is a social learning strategy whereby learners tend to acquire the cultural variants of successful individuals. I develop a general model of success-biased social learning for discrete cultural traits with stochastic payoffs, and investigate its dynamics when only two variants are present. I find that success bias inherently favors rare variants, and consequently performs worse than unbiased imitation (i.e. random copying) when success payoffs are at least mildly stochastic and the optimal variant is common. Because of this weakness, success bias fails to replace unbiased imitation in an evolutionary model when selection is fairly weak or when the environment is relatively stable, and sometimes fails to invade at all. I briefly discuss the optimal strength of success bias, the complicated nature of defining success in social learning contexts, and the value of variant frequency as an important source of information to social learners. I conclude with predictions regarding the prevalence of success bias in different behavioral domains.

Suggested Citation

  • Baldini, Ryan, 2012. "Success-biased social learning: Cultural and evolutionary dynamics," Theoretical Population Biology, Elsevier, vol. 82(3), pages 222-228.
  • Handle: RePEc:eee:thpobi:v:82:y:2012:i:3:p:222-228
    DOI: 10.1016/j.tpb.2012.06.005
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    References listed on IDEAS

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    1. Schlag, Karl H., 1999. "Which one should I imitate?," Journal of Mathematical Economics, Elsevier, vol. 31(4), pages 493-522, May.
    2. McElreath, Richard & Boyd, Robert, 2007. "Mathematical Models of Social Evolution," University of Chicago Press Economics Books, University of Chicago Press, number 9780226558264, October.
    3. 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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    Cited by:

    1. Baldini, Ryan, 2013. "Two success-biased social learning strategies," Theoretical Population Biology, Elsevier, vol. 86(C), pages 43-49.
    2. Takahashi, Takuya & Ihara, Yasuo, 2019. "Cultural and evolutionary dynamics with best-of-k learning when payoffs are uncertain," Theoretical Population Biology, Elsevier, vol. 128(C), pages 27-38.
    3. Clark, Matt & Andrews, Jeffrey & Hillis, Vicken, 2022. "A quantitative application of diffusion of innovations for modeling the spread of conservation behaviors," Ecological Modelling, Elsevier, vol. 473(C).

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