Krasnow Max M, Delton Andrew W, Cosmides Leda, Tooby John
Department of Psychology, Harvard University, Cambridge, Massachusetts, United States of America.
Department of Political Science, College of Business, Center for Behavioral Political Economy, Stony Brook University, Stony Brook, New York, United States of America.
PLoS One. 2015 Apr 20;10(4):e0124561. doi: 10.1371/journal.pone.0124561. eCollection 2015.
Humans everywhere cooperate in groups to achieve benefits not attainable by individuals. Individual effort is often not automatically tied to a proportionate share of group benefits. This decoupling allows for free-riding, a strategy that (absent countermeasures) outcompetes cooperation. Empirically and formally, punishment potentially solves the evolutionary puzzle of group cooperation. Nevertheless, standard analyses appear to show that punishment alone is insufficient, because second-order free riders (those who cooperate but do not punish) can be shown to outcompete punishers. Consequently, many have concluded that other processes, such as cultural or genetic group selection, are required. Here, we present a series of agent-based simulations that show that group cooperation sustained by punishment easily evolves by individual selection when you introduce into standard models more biologically plausible assumptions about the social ecology and psychology of ancestral humans. We relax three unrealistic assumptions of past models. First, past models assume all punishers must punish every act of free riding in their group. We instead allow punishment to be probabilistic, meaning punishers can evolve to only punish some free riders some of the time. This drastically lowers the cost of punishment as group size increases. Second, most models unrealistically do not allow punishment to recruit labor; punishment merely reduces the punished agent's fitness. We instead realistically allow punished free riders to cooperate in the future to avoid punishment. Third, past models usually restrict agents to interact in a single group their entire lives. We instead introduce realistic social ecologies in which agents participate in multiple, partially overlapping groups. Because of this, punitive tendencies are more expressed and therefore more exposed to natural selection. These three moves toward greater model realism reveal that punishment and cooperation easily evolve by direct selection--even in sizeable groups.
世界各地的人类都会进行群体合作，以获取个体无法实现的利益。个体的努力往往不会自动与群体利益的相应份额挂钩。这种脱钩使得搭便车行为成为可能，这是一种（在没有应对措施的情况下）比合作更具竞争力的策略。从经验和形式上看，惩罚有可能解决群体合作的进化难题。然而，标准分析似乎表明，仅靠惩罚是不够的，因为二阶搭便车者（即那些合作但不惩罚的人）可以证明比惩罚者更具竞争力。因此，许多人得出结论，需要其他过程，如文化或基因群体选择。在这里，我们提出了一系列基于主体的模拟，结果表明，当你在标准模型中引入关于原始人类社会生态和心理的更符合生物学现实的假设时，由惩罚维持的群体合作很容易通过个体选择而进化。我们放宽了过去模型的三个不现实假设。第一，过去的模型假设所有惩罚者必须惩罚其群体中的每一次搭便车行为。我们改为允许惩罚具有概率性，这意味着惩罚者可以进化为只在某些时候惩罚一些搭便车者。随着群体规模的增加，这大大降低了惩罚成本。第二，大多数模型不现实地不允许惩罚招募劳动力；惩罚仅仅降低了受惩罚个体的适应性。我们改为现实地允许受惩罚的搭便车者未来进行合作以避免惩罚。第三，过去的模型通常限制主体在其一生中只在一个群体中互动。我们改为引入现实的社会生态，其中主体参与多个部分重叠的群体。因此，惩罚倾向得到更充分的表达，因此更容易受到自然选择的影响。这三个使模型更接近现实的举措表明，惩罚和合作很容易通过直接选择而进化——即使在规模较大的群体中也是如此。
