Program for Evolutionary Dynamics, Department of Psychology, Harvard University, Cambridge, MA 02139, USA.
Proc Natl Acad Sci U S A. 2013 Feb 12;110(7):2581-6. doi: 10.1073/pnas.1214167110. Epub 2013 Jan 22.
Classical economic models assume that people are fully rational and selfish, while experiments often point to different conclusions. A canonical example is the Ultimatum Game: one player proposes a division of a sum of money between herself and a second player, who either accepts or rejects. Based on rational self-interest, responders should accept any nonzero offer and proposers should offer the smallest possible amount. Traditional, deterministic models of evolutionary game theory agree: in the one-shot anonymous Ultimatum Game, natural selection favors low offers and demands. Experiments instead show a preference for fairness: often responders reject low offers and proposers make higher offers than needed to avoid rejection. Here we show that using stochastic evolutionary game theory, where agents make mistakes when judging the payoffs and strategies of others, natural selection favors fairness. Across a range of parameters, the average strategy matches the observed behavior: proposers offer between 30% and 50%, and responders demand between 25% and 40%. Rejecting low offers increases relative payoff in pairwise competition between two strategies and is favored when selection is sufficiently weak. Offering more than you demand increases payoff when many strategies are present simultaneously and is favored when mutation is sufficiently high. We also perform a behavioral experiment and find empirical support for these theoretical findings: uncertainty about the success of others is associated with higher demands and offers; and inconsistency in the behavior of others is associated with higher offers but not predictive of demands. In an uncertain world, fairness finishes first.
经典的经济模型假设人们是完全理性和自私的,而实验往往指向不同的结论。一个典型的例子是最后通牒博弈:一名玩家提出将一笔钱在自己和第二名玩家之间分配,第二名玩家可以接受或拒绝。基于理性的自利,回应者应该接受任何非零的报价,而提议者应该提供尽可能少的金额。传统的、确定性的进化博弈论模型也同意这一点:在一次性匿名的最后通牒博弈中,自然选择有利于低报价和高要求。然而,实验结果显示出对公平的偏好:回应者经常拒绝低报价,而提议者会提出高于避免被拒绝所需的金额。在这里,我们表明,使用随机进化博弈论,当代理人在判断他人的收益和策略时犯错误时,自然选择有利于公平。在一系列参数中,平均策略与观察到的行为相匹配:提议者提供的报价在 30%到 50%之间,回应者的要求在 25%到 40%之间。拒绝低报价会增加两种策略在两两竞争中的相对收益,当选择足够弱时,这种策略会受到青睐。提供比你要求的更多的收益会增加当许多策略同时存在时的收益,当突变足够高时,这种策略会受到青睐。我们还进行了一项行为实验,并为这些理论发现找到了经验支持:对他人成功的不确定性与更高的要求和报价有关;他人行为的不一致性与更高的报价有关,但不能预测要求。在一个不确定的世界里,公平是第一位的。