论文标题
在经验丰富的回报动力下，囚犯困境中叛逃的不稳定
Instability of Defection in the Prisoner's Dilemma Under Best Experienced Payoff Dynamics
论文作者
论文摘要
我们研究人口动态，每个修订代理都会测试每个策略k时间，每个试验都是针对新绘制的对手的，并选择了平均收益最高的策略。当k = 1时，在囚犯的困境中，叛逃在全球范围内稳定。相比之下，当k> 1时，我们表明存在一个全球稳定的状态，在该状态下，试剂的概率在28％至50％之间。接下来，我们描述了一般游戏中严格平衡的稳定性。我们的结果表明，k> 1的经验合理病例与文献中通常研究的k = 1的情况可以产生质量不同的预测。
We study population dynamics under which each revising agent tests each strategy k times, with each trial being against a newly drawn opponent, and chooses the strategy whose mean payoff was highest. When k = 1, defection is globally stable in the prisoner`s dilemma. By contrast, when k > 1 we show that there exists a globally stable state in which agents cooperate with probability between 28% and 50%. Next, we characterize stability of strict equilibria in general games. Our results demonstrate that the empirically plausible case of k > 1 can yield qualitatively different predictions than the case of k = 1 that is commonly studied in the literature.
