Meiji Institute for Advanced Study of Mathematical Sciences, Meiji University, 1-1-1 Higashimita, Tamaku, Kawasaki, Kanagawa 214-8571, Japan.
Hum Nat. 2012 Dec;23(4):386-418. doi: 10.1007/s12110-012-9151-y.
Long before the origins of agriculture human ancestors had expanded across the globe into an immense variety of environments, from Australian deserts to Siberian tundra. Survival in these environments did not principally depend on genetic adaptations, but instead on evolved learning strategies that permitted the assembly of locally adaptive behavioral repertoires. To develop hypotheses about these learning strategies, we have modeled the evolution of learning strategies to assess what conditions and constraints favor which kinds of strategies. To build on prior work, we focus on clarifying how spatial variability, temporal variability, and the number of cultural traits influence the evolution of four types of strategies: (1) individual learning, (2) unbiased social learning, (3) payoff-biased social learning, and (4) conformist transmission. Using a combination of analytic and simulation methods, we show that spatial-but not temporal-variation strongly favors the emergence of conformist transmission. This effect intensifies when migration rates are relatively high and individual learning is costly. We also show that increasing the number of cultural traits above two favors the evolution of conformist transmission, which suggests that the assumption of only two traits in many models has been conservative. We close by discussing how (1) spatial variability represents only one way of introducing the low-level, nonadaptive phenotypic trait variation that so favors conformist transmission, the other obvious way being learning errors, and (2) our findings apply to the evolution of conformist transmission in social interactions. Throughout we emphasize how our models generate empirical predictions suitable for laboratory testing.
早在农业起源之前,人类祖先就已经扩展到了全球范围内的各种环境中,从澳大利亚的沙漠到西伯利亚的冻原。这些环境中的生存并不主要依赖于遗传适应,而是依赖于进化的学习策略,这些策略允许组装出具有局部适应性的行为组合。为了对这些学习策略提出假设,我们对学习策略的进化进行了建模,以评估哪些条件和限制有利于哪种策略。为了在之前的工作基础上更进一步,我们重点澄清了空间变异性、时间变异性和文化特征数量如何影响四种策略的进化:(1)个体学习,(2)无偏社会学习,(3)收益偏置社会学习和(4)从众传播。我们使用分析和模拟方法的组合表明,空间变化而不是时间变化强烈有利于从众传播的出现。当迁移率相对较高且个体学习成本较高时,这种影响会加剧。我们还表明,将文化特征的数量增加到两个以上有利于从众传播的进化,这表明许多模型中仅假设两个特征是保守的。最后,我们讨论了(1)空间变异性仅代表引入有利于从众传播的低水平、非适应性表型变异的一种方式,另一种明显的方式是学习错误,以及(2)我们的发现如何适用于社会互动中从众传播的进化。在整个过程中,我们强调了我们的模型如何生成适合实验室测试的经验预测。