London Mathematical Laboratory, 8 Margravine Gardens, London W6 8RH, UK.
Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA.
Philos Trans A Math Phys Eng Sci. 2022 Jul 11;380(2227):20200425. doi: 10.1098/rsta.2020.0425. Epub 2022 May 23.
When two entities cooperate by sharing resources, one relinquishes something of value to the other. This apparent altruism is frequently observed in nature. Why? Classical treatments assume circumstances where combining resources creates an immediate benefit, e.g. through complementarity or thresholds. Here we ask whether cooperation is predictable without such circumstances. We study a model in which resources self-multiply with fluctuations, a null model of a range of phenomena from viral spread to financial investment. Two fundamental growth rates exist: the ensemble-average growth rate, achieved by the average resources of a large population; and the time-average growth rate, achieved by individual resources over a long time. As a consequence of non-ergodicity, the latter is lower than the former by a term which depends on fluctuation size. Repeated pooling and sharing of resources reduces the effective size of fluctuations and increases the time-average growth rate, which approaches the ensemble-average growth rate in the many-cooperator limit. Therefore, cooperation is advantageous in our model for the simple reason that those who do it grow faster than those who do not. We offer this as a candidate explanation for observed cooperation in rudimentary environments, and as a behavioural baseline for cooperation more generally. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.
当两个实体通过共享资源进行合作时,一方会向另一方放弃有价值的东西。这种明显的利他主义在自然界中经常被观察到。为什么?经典的处理方法假设在某些情况下,组合资源会立即带来好处,例如通过互补性或阈值。在这里,我们询问在没有这种情况的情况下合作是否可以预测。我们研究了一种模型,其中资源随波动自我繁殖,这是从病毒传播到金融投资等一系列现象的零模型。存在两种基本增长率:集合平均增长率,由大量资源的平均资源实现;以及时间平均增长率,由个体资源在很长一段时间内实现。由于非遍历性,后者比前者低一个取决于波动大小的项。资源的重复汇集和共享会降低波动的有效大小,并增加时间平均增长率,在多合作者极限下,时间平均增长率接近集合平均增长率。因此,合作在我们的模型中是有利的,原因很简单,即那些合作的人比那些不合作的人增长得更快。我们将其作为在原始环境中观察到的合作的候选解释,并作为更普遍的合作的行为基准。本文是“复杂物理和社会技术系统中的涌现现象:从细胞到社会”主题问题的一部分。