Title of article
Do social learning and conformist bias coevolve? Henrich and Boyd revisited
Author/Authors
Joe Yuichiro Wakano، نويسنده , , Kenichi Aoki، نويسنده ,
Issue Information
دوماهنامه با شماره پیاپی سال 2007
Pages
9
From page
504
To page
512
Abstract
We studied the coevolution of social learning and conformist bias in a modified version of the Henrich and Boyd [1998. The evolution of conformist transmission and the emergence of between-group differences. Evol. Hum. Behav. 19, 215–241] model that nevertheless preserves its essential features. The convergent stable strategies (CSS) are identified by a numerical adaptive dynamics method and then checked for evolutionary stability. A strategy that is simultaneously a CSS and an ESS is called an attractive evolutionarily stable strategy (AESS). Our main findings are as follows. First, the AESS reliance on social learning is monotone increasing in the fixed interval between environmental changes and monotone decreasing in the quality of environmental information. Second, the AESS strength of conformist bias is monotone non-increasing in the fixed interval between environmental changes and monotone non-decreasing in the quality of environmental information. The first observation is in agreement with Henrich and Boyd (1998), but the second is in direct contradiction. In addition, we conducted Monte Carlo simulations as in Henrich and Boyd (1998), which supported our findings. We believe that the reason for the discrepancy with regard to the strength of conformist bias is that Henrich and Boyd (1998) did not allow a sufficient number of iterations for true convergence to occur. In conclusion, the conditions favoring a heavy reliance on social learning are not the same as those favoring a strong conformist bias.
Keywords
Adaptive dynamics , Adaptive step size Runge–Kutta method , Attractive ESS
Journal title
Theoretical Population Biology
Serial Year
2007
Journal title
Theoretical Population Biology
Record number
774031
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