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Fitness landscapes among many options under social influence

Caiado, C.C.S.; Brock, W.A.; Bentley, R.A.; O'Brien, M.J.

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W.A. Brock

R.A. Bentley

M.J. O'Brien


Cultural learning represents a novel problem in that an optimal decision depends not only on intrinsic utility of the decision/behavior but also on transparency of costs and benefits, the degree of social versus individual learning, and the relative popularity of each possible choice in a population. In terms of a fitness-landscape function, this recursive relationship means that multiple equilibria can exist. Here we use discrete-choice theory to construct a fitness-landscape function for a bi-axial decision-making map that plots the magnitude of social influence in the learning process against the costs and payoffs of decisions. Specifically, we use econometric and statistical methods to estimate not only the fitness function but also movements along the map axes. To search for these equilibria, we employ a hill-climbing algorithm that leads to the expected values of optimal decisions, which we define as peaks on the fitness landscape. We illustrate how estimation of a measure of transparency, a measure of social influence, and the associated fitness landscape can be accomplished using panel data sets.


Caiado, C., Brock, W., Bentley, R., & O'Brien, M. (2016). Fitness landscapes among many options under social influence. Journal of Theoretical Biology, 405, 5-16.

Journal Article Type Article
Acceptance Date Dec 17, 2015
Online Publication Date Feb 2, 2016
Publication Date Sep 21, 2016
Deposit Date Jun 15, 2016
Publicly Available Date Aug 11, 2017
Journal Journal of Theoretical Biology
Print ISSN 0022-5193
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 405
Article Number S0022-5193(16)00014-X
Pages 5-16


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