相互依赖网络中耦合进化博弈的有偏模仿
Biased imitation in coupled evolutionary games in interdependent networks
摘要：
我们探讨两个游戏的进化动力学-囚徒困境和雪堆游戏-发挥不同的网络（层）的相互依存的网络。在这些网络中，相互对立的个体之间的模仿和互动是通过相互联系建立起来的。我们探讨了一个更新规则，其中修订的战略是一个有偏见的模仿过程：个人模仿邻居从同一层的概率p，和邻居从第二层的互补概率1 -p。我们证明，一个小的减少p从p = 1（这对应于禁止层之间的战略转移）是足以促进合作的囚徒困境子群。另一方面，这不利于雪堆游戏亚群的合作。我们提供了广泛的计算机模拟的情况下，层建模为定期随机网络的结果，并支持这项研究的分析结果耦合良好的混合人口。
英文摘要：
We explore the evolutionary dynamics of two games - the Prisoner's Dilemma and the Snowdrift Game - played within distinct networks (layers) of interdependent networks. In these networks imitation and interaction between individuals of opposite layers is established through interlinks. We explore an update rule in which revision of strategies is a biased imitation process: individuals imitate neighbors from the same layer with probability p, and neighbors from the second layer with complementary probability 1 - p. We demonstrate that a small decrease of p from p = 1 (which corresponds to forbidding strategy transfer between layers) is sufficient to promote cooperation in the Prisoner's Dilemma subpopulation. This, on the other hand, is detrimental for cooperation in the Snowdrift Game subpopulation. We provide results of extensive computer simulations for the case in which layers are modelled as regular random networks, and support this study with analytical results for coupled well-mixed populations.
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。
