Modelling the spread of innovation in wild birds.
We apply three plausible algorithms in agent-based computer simulations to recent experiments on social learning in wild birds. Although some of the phenomena are simulated by all three learning algorithms, several manifestations of social conformity bias are simulated by only the approximate majority (AM) algorithm, which has roots in chemistry, molecular biology and theoretical computer science. The simulations generate testable predictions and provide several explanatory insights into the diffusion of innovation through a population. The AM algorithm's success raises the possibility of its usefulness in studying group dynamics more generally, in several different scientific domains. Our differential-equation model matches simulation results and provides mathematical insights into the dynamics of these algorithms.
['Shultz|Thomas R|TR|0000-0003-2413-8840', 'Montrey|Marcel|M|', 'Aplin|Lucy M|LM|0000-0001-5367-826X']
D000465:Algorithms D000818:Animals D000835:Animals, Wild D001522:Behavior, Animal D001717:Birds D003198:Computer Simulation D007858:Learning D008954:Models, Biological D012919:Social Behavior
agent-based computer simulation social learning conformity bias animal culture differential equations innovation diffusion