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社会学习与个体学习的进化:无限岛屿模型视角

Evolution of social versus individual learning in an infinite island model.

机构信息

Department of Biological Sciences, The University of Tokyo, Bunkyoku, Tokyo 113-0033, Japan.

出版信息

Evolution. 2012 May;66(5):1624-35. doi: 10.1111/j.1558-5646.2011.01541.x. Epub 2012 Jan 12.

Abstract

We model the evolution of learning in a population composed of infinitely many, finite-sized islands connected by migration. We assume that there are two discrete strategies, social and individual learning, and that the environment is spatially homogeneous but varies temporally in a periodic or stochastic manner. Using a population-genetic approximation technique, we derive a mathematical condition for the two strategies to coexist stably and the equilibrium frequency of social learners under stable coexistence. Analytical and numerical results both reveal that social learners are favored when island size is large or migration rate between islands is high, suggesting that spatial subdivision disfavors social learners. We also show that the average fecundity of the population under stable coexistence of the two strategies is in general lower than that in the absence of social learners and is minimized at an intermediate migration rate.

摘要

我们在由通过迁移连接的无限多个有限大小的岛屿组成的种群中模拟学习的演化。我们假设存在两种离散策略,即社会学习和个体学习,并且环境在空间上是均匀的,但在时间上以周期性或随机的方式变化。使用种群遗传近似技术,我们推导出了两种策略稳定共存的数学条件,以及在稳定共存下社会学习者的平衡频率。分析和数值结果都表明,当岛屿大小较大或岛屿之间的迁移率较高时,社会学习者更有利,这表明空间细分不利于社会学习者。我们还表明,在两种策略稳定共存下,种群的平均繁殖力通常低于没有社会学习者的情况下,并且在中间迁移率下最小化。

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