Determinants of public cooperation in multiplex networks
Determinants of public cooperation in multiplex networks
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DOI：
10.1088/1367-2630/aa6ea1
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发表时间：
2017-07-12
影响因子：
3.3
通讯作者：
Latora, Vito
中科院分区：
文献类型：
--
作者：
Battiston, Federico;Perc, Matjaz;Latora, Vito
进化博弈论和统计物理学之间的协同作用显著提高了我们对结构群体中公共合作的理解。特别是多路网络，为网络科学提供了理论框架，使我们能够用数学方法描述人类社会特征的丰富互动结构。虽然研究表明，多路网络可以增强合作的弹性，但层结构的重叠与相应博弈的控制参数之间的相互作用尚未得到研究。为此，我们考虑了多路网络上的公共物品博弈，揭示了层数和链路重叠的作用，以及不同层中不同协同因素对合作开始的影响。我们表明，只有当显著的边缘重叠与至少一层能够通过足够高的协同因子维持某些合作相结合时，才会出现增强的公共合作。在没有这两个条件的情况下，多路网络的合作演化取决于传统网络互惠的边界，而没有增强的弹性。这些结果提醒我们不要过于乐观地预测，即多个社会领域的存在本身可能促进合作，它们有助于我们更好地理解分层社会系统中亲社会行为背后的复杂性。
Synergies between evolutionary game theory and statistical physics have significantly improved our understanding of public cooperation in structured populations. Multiplex networks, in particular, provide the theoretical framework within network science that allows us to mathematically describe the rich structure of interactions characterizing human societies. While research has shown that multiplex networks may enhance the resilience of cooperation, the interplay between the overlap in the structure of the layers and the control parameters of the corresponding games has not yet been investigated. With this aim, we consider here the public goods game on a multiplex network, and we unveil the role of the number of layers and the overlap of links, as well as the impact of different synergy factors in different layers, on the onset of cooperation. We show that enhanced public cooperation emerges only when a significant edge overlap is combined with at least one layer being able to sustain some cooperation by means of a sufficiently high synergy factor. In the absence of either of these conditions, the evolution of cooperation in multiplex networks is determined by the bounds of traditional network reciprocity with no enhanced resilience. These results caution against overly optimistic predictions that the presence of multiple social domains may in itself promote cooperation, and they help us better understand the complexity behind prosocial behavior in layered social systems.