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Topological Traps Control Flow on Real Networks: The Case of Coordination Failures

机译:实际网络上的拓扑陷阱控制流:协调失败的情况

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摘要

We study evolutionary games in real social networks, with a focus on coordination games. We find that populations fail to coordinate in the same behavior for a wide range of parameters, a novel phenomenon not observed in most artificial model networks. We show that this result arises from the relevance of correlations beyond the first neighborhood, in particular from topological traps formed by links between nodes of different degrees in regions with few or no redundant paths. This specificity of real networks has not been modeled so far with synthetic networks. We thus conclude that model networks must be improved to include these mesoscopic structures, in order to successfully address issues such as the emergence of cooperation in real societies. We finally show that topological traps are a very generic phenomenon that may arise in very many different networks and fields, such as opinion models, spread of diseases or ecological networks.
机译:我们研究真实社交网络中的进化游戏,重点是协调游戏。我们发现种群无法针对广泛的参数协调相同的行为,这是在大多数人工模型网络中未观察到的新现象。我们表明,该结果来自于超出第一邻域的相关性的相关性,特别是由拓扑图陷阱所形成,该拓扑图陷阱是由很少或没有冗余路径的区域中不同程度的节点之间的链接形成的。到目前为止,还没有使用合成网络对真实网络的这种特殊性进行建模。因此,我们得出结论,必须改进模型网络以包括这些介观结构,以便成功解决诸如在现实社会中出现合作等问题。我们最终表明,拓扑陷阱是一种非常普遍的现象,可能会在许多不同的网络和领域中出现,例如意见模型,疾病传播或生态网络。

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