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异质性活动和群落结构对社交网络中合作者进化成功的影响。

Impact of heterogeneous activity and community structure on the evolutionary success of cooperators in social networks.

作者信息

Wu Zhi-Xi, Rong Zhihai, Yang Han-Xin

机构信息

Institute of Computational Physics and Complex Systems, Lanzhou University, Lanzhou, Gansu 730000, China.

CompleX Lab, Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China and Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2015 Jan;91(1):012802. doi: 10.1103/PhysRevE.91.012802. Epub 2015 Jan 5.

Abstract

Recent empirical studies suggest that heavy-tailed distributions of human activities are universal in real social dynamics [L. Muchnik, S. Pei, L. C. Parra, S. D. S. Reis, J. S. Andrade Jr., S. Havlin, and H. A. Makse, Sci. Rep. 3, 1783 (2013)]. On the other hand, community structure is ubiquitous in biological and social networks [M. E. J. Newman, Nat. Phys. 8, 25 (2012)]. Motivated by these facts, we here consider the evolutionary prisoner's dilemma game taking place on top of a real social network to investigate how the community structure and the heterogeneity in activity of individuals affect the evolution of cooperation. In particular, we account for a variation of the birth-death process (which can also be regarded as a proportional imitation rule from a social point of view) for the strategy updating under both weak and strong selection (meaning the payoffs harvested from games contribute either slightly or heavily to the individuals' performance). By implementing comparative studies, where the players are selected either randomly or in terms of their actual activities to play games with their immediate neighbors, we figure out that heterogeneous activity benefits the emergence of collective cooperation in a harsh environment (the action for cooperation is costly) under strong selection, whereas it impairs the formation of altruism under weak selection. Moreover, we find that the abundance of communities in the social network can evidently foster the formation of cooperation under strong selection, in contrast to the games evolving on randomized counterparts. Our results are therefore helpful for us to better understand the evolution of cooperation in real social systems.

摘要

近期的实证研究表明,人类活动的重尾分布在真实的社会动态中普遍存在[L. 穆奇尼克、S. 裴、L. C. 帕拉、S. D. S. 雷斯、J. S. 安德拉德 Jr.、S. 哈夫林和H. A. 马克塞,《科学报告》3,1783 (2013)]。另一方面,群落结构在生物和社会网络中无处不在[M. E. J. 纽曼,《自然物理学》8,25 (2012)]。受这些事实的启发,我们在此考虑在真实社会网络之上进行的进化囚徒困境博弈,以研究群落结构和个体活动的异质性如何影响合作的进化。具体而言,我们考虑了生死过程的一种变体(从社会角度来看,这也可被视为一种比例模仿规则),用于在弱选择和强选择下更新策略(意味着从博弈中获得的收益对个体表现的贡献要么轻微要么显著)。通过进行比较研究,即玩家要么被随机选择,要么根据其实际活动被选择与直接邻居进行博弈,我们发现,在强选择下,异质性活动有利于在恶劣环境(合作行为成本高昂)中出现集体合作,而在弱选择下,它会损害利他主义的形成。此外,我们发现,与在随机化对应网络上进行的博弈相比,社会网络中群落的丰富性在强选择下能明显促进合作的形成。因此,我们的结果有助于我们更好地理解真实社会系统中合作的进化。

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