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arXiv 0902.1447physics.soc-ph
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网络上的进化博弈与复制动态下的支付不变性

Evolutionary Games on Networks and Payoff Invariance Under Replicator Dynamics

Leslie Luthi, Marco Tomassini, Enea Pestelacci

摘要:

常用的累积支付方案是不恒定的支付值的移位时,局部应用在度非齐次人口结构。我们提出了一个适当修改的支付方案,我们正式和数值模拟表明,它离开复制动力学不变的仿射变换的游戏支付矩阵。然后,我们的经验表明,使用修改后的支付方案,一个有趣的合作量可以达到三个典型的非合作两人游戏的人口结构,根据图,有一个显着的程度不均匀性,类似于社会中发现的实际图形。这三个博弈是囚徒困境、鹰鸽博弈和猎鹿博弈。这证实了以前的重要观察,在某些条件下,合作可能会出现在这样的网络结构的人口,即使标准的复制动力学混合人口规定的均衡,其中合作是完全不存在的囚徒困境,它是不太普遍的其他两个游戏。

英文摘要:

The commonly used accumulated payoff scheme is not invariant with respect to shifts of payoff values when applied locally in degree-inhomogeneous population structures. We propose a suitably modified payoff scheme and we show both formally and by numerical simulation, that it leaves the replicator dynamics invariant with respect to affine transformations of the game payoff matrix. We then show empirically that, using the modified payoff scheme, an interesting amount of cooperation can be reached in three paradigmatic non-cooperative two-person games in populations that are structured according to graphs that have a marked degree inhomogeneity, similar to actual graphs found in society. The three games are the Prisoner's Dilemma, the Hawks-Doves and the Stag-Hunt. This confirms previous important observations that, under certain conditions, cooperation may emerge in such network-structured populations, even though standard replicator dynamics for mixing populations prescribes equilibria in which cooperation is totally absent in the Prisoner's Dilemma, and it is less widespread in the other two games.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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