Martinez-Vaquero Luis A, Han The Anh, Pereira Luís Moniz, Lenaerts Tom
AI lab, Computer Science Department, Vrije Universiteit Brussel, Pleinlaan 2, Brussels, 1050 Belgium.
MLG, Département d'Informatique, Université Libre de Bruxelles, Boulevard du Triomphe CP212, Brussels, 1050 Belgium.
Sci Rep. 2015 Jun 9;5:10639. doi: 10.1038/srep10639.
Making agreements on how to behave has been shown to be an evolutionarily viable strategy in one-shot social dilemmas. However, in many situations agreements aim to establish long-term mutually beneficial interactions. Our analytical and numerical results reveal for the first time under which conditions revenge, apology and forgiveness can evolve and deal with mistakes within ongoing agreements in the context of the Iterated Prisoners Dilemma. We show that, when the agreement fails, participants prefer to take revenge by defecting in the subsisting encounters. Incorporating costly apology and forgiveness reveals that, even when mistakes are frequent, there exists a sincerity threshold for which mistakes will not lead to the destruction of the agreement, inducing even higher levels of cooperation. In short, even when to err is human, revenge, apology and forgiveness are evolutionarily viable strategies which play an important role in inducing cooperation in repeated dilemmas.
在一次性社会困境中,就行为方式达成协议已被证明是一种进化上可行的策略。然而,在许多情况下,协议旨在建立长期互利的互动关系。我们的分析和数值结果首次揭示了在重复囚徒困境的背景下,报复、道歉和宽恕在何种条件下能够进化并处理现有协议中的失误。我们表明,当协议失效时,参与者更倾向于在后续相遇中通过背叛来进行报复。纳入代价高昂的道歉和宽恕表明,即使失误频繁,也存在一个真诚度阈值,在这个阈值下失误不会导致协议的破裂,反而会促使更高水平的合作。简而言之,即使人都会犯错,但报复、道歉和宽恕是进化上可行的策略,它们在重复困境中诱导合作方面发挥着重要作用。