Arbilly Michal, Laland Kevin N
School of Biology, University of St Andrews, UK.
School of Biology, University of St Andrews, UK.
Theor Popul Biol. 2014 Feb;91:50-7. doi: 10.1016/j.tpb.2013.09.006. Epub 2013 Sep 14.
Social learning mechanisms are widely thought to vary in their degree of complexity as well as in their prevalence in the natural world. While learning the properties of a stimulus that generalize to similar stimuli at other locations (stimulus enhancement) prima facie appears more useful to an animal than learning about a specific stimulus at a specific location (local enhancement), empirical evidence suggests that the latter is much more widespread in nature. Simulating populations engaged in a producer-scrounger game, we sought to deploy mathematical models to identify the adaptive benefits of reliance on local enhancement and/or stimulus enhancement, and the alternative conditions favoring their evolution. Surprisingly, we found that while stimulus enhancement readily evolves, local enhancement is advantageous only under highly restricted conditions: when generalization of information was made unreliable or when error in social learning was high. Our results generate a conundrum over how seemingly conflicting empirical and theoretical findings can be reconciled. Perhaps the prevalence of local enhancement in nature is due to stimulus enhancement costs independent of the learning task itself (e.g. predation risk), perhaps natural habitats are often characterized by unreliable yet highly rewarding payoffs, or perhaps local enhancement occurs less frequently, and stimulus enhancement more frequently, than widely believed.
社会学习机制被广泛认为在其复杂程度以及在自然界中的普遍程度上存在差异。虽然学习一种能推广到其他位置的类似刺激物的属性(刺激增强)表面上对动物来说似乎比学习特定位置的特定刺激物(局部增强)更有用,但经验证据表明后者在自然界中更为普遍。通过模拟参与生产者 - 掠夺者游戏的群体,我们试图运用数学模型来确定依赖局部增强和/或刺激增强的适应性益处,以及有利于它们进化的其他条件。令人惊讶的是,我们发现虽然刺激增强很容易进化,但局部增强仅在高度受限的条件下才具有优势:当信息的泛化变得不可靠或社会学习中的误差很大时。我们的结果引发了一个难题,即如何调和看似相互矛盾的实证和理论发现。也许自然界中局部增强的普遍存在是由于与学习任务本身无关的刺激增强成本(例如捕食风险),也许自然栖息地通常具有不可靠但回报丰厚的收益特征,或者也许局部增强的发生频率比广泛认为的要低,而刺激增强的发生频率更高。