ETH Zurich, Zurich, Switzerland.
PLoS Comput Biol. 2010 Apr 29;6(4):e1000758. doi: 10.1371/journal.pcbi.1000758.
Situations where individuals have to contribute to joint efforts or share scarce resources are ubiquitous. Yet, without proper mechanisms to ensure cooperation, the evolutionary pressure to maximize individual success tends to create a tragedy of the commons (such as over-fishing or the destruction of our environment). This contribution addresses a number of related puzzles of human behavior with an evolutionary game theoretical approach as it has been successfully used to explain the behavior of other biological species many times, from bacteria to vertebrates. Our agent-based model distinguishes individuals applying four different behavioral strategies: non-cooperative individuals ("defectors"), cooperative individuals abstaining from punishment efforts (called "cooperators" or "second-order free-riders"), cooperators who punish non-cooperative behavior ("moralists"), and defectors, who punish other defectors despite being non-cooperative themselves ("immoralists"). By considering spatial interactions with neighboring individuals, our model reveals several interesting effects: First, moralists can fully eliminate cooperators. This spreading of punishing behavior requires a segregation of behavioral strategies and solves the "second-order free-rider problem". Second, the system behavior changes its character significantly even after very long times ("who laughs last laughs best effect"). Third, the presence of a number of defectors can largely accelerate the victory of moralists over non-punishing cooperators. Fourth, in order to succeed, moralists may profit from immoralists in a way that appears like an "unholy collaboration". Our findings suggest that the consideration of punishment strategies allows one to understand the establishment and spreading of "moral behavior" by means of game-theoretical concepts. This demonstrates that quantitative biological modeling approaches are powerful even in domains that have been addressed with non-mathematical concepts so far. The complex dynamics of certain social behaviors become understandable as the result of an evolutionary competition between different behavioral strategies.
在需要共同努力或共享稀缺资源的情况下,个体往往需要做出贡献。然而,如果没有适当的机制来确保合作,那么最大限度地追求个人成功的进化压力往往会导致公地悲剧(例如过度捕捞或环境破坏)。本研究采用进化博弈论方法来解决许多与人类行为相关的难题,因为该方法已多次成功地用于解释其他生物物种的行为,从细菌到脊椎动物。我们的基于代理的模型区分了应用四种不同行为策略的个体:不合作的个体(“背叛者”)、不合作但不进行惩罚努力的合作个体(称为“合作者”或“二阶搭便车者”)、惩罚不合作行为的合作者(“道德主义者”)以及尽管自己不合作但会惩罚其他背叛者的背叛者(“不道德主义者”)。通过考虑与相邻个体的空间相互作用,我们的模型揭示了几个有趣的效应:第一,道德主义者可以完全消灭合作者。这种惩罚行为的传播需要行为策略的隔离,并解决了“二阶搭便车问题”。第二,即使经过很长时间,系统行为也会发生显著变化(“笑到最后的人笑得最好”效应)。第三,即使存在大量的背叛者,也可以极大地加速道德主义者对不惩罚的合作者的胜利。第四,为了取得成功,道德主义者可能会从不道德主义者那里受益,这看起来像是一种“不圣洁的合作”。我们的研究结果表明,考虑惩罚策略可以通过博弈论概念来理解“道德行为”的建立和传播。这表明,即使在迄今为止采用非数学概念的领域,定量生物学建模方法也是强大的。某些社会行为的复杂动态可以理解为不同行为策略之间的进化竞争的结果。