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相互影响的双层网络上的进化博弈

Evolutionary game on mutually influenceing double-layer network.

作者信息

Hao Qinzhi, Yang Haochun, Sun Yao, Xu Tao, Huang Huang

机构信息

Air Force Engineering University, Xi'an, China.

School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China.

出版信息

PLoS One. 2025 Jan 31;20(1):e0317923. doi: 10.1371/journal.pone.0317923. eCollection 2025.

Abstract

In recent years, coupled double-layer networks have played an increasingly critical role in evolutionary game theory. Research indicates that these networks more accurately reflect real-world relationships between individuals. However, current studies mainly focus on unidirectional influence within double-layer networks. Based on this, we propose a strongly coupled double-layer network cooperation evolution model. Strength individuals are located in the upper network layer, influencing the strategy choices of ordinary individuals in the lower layer, and vice versa. Monte Carlo simulations show that strength individuals can effectively enhance overall group cooperation. Under low temptation to defect, the group maintains a high cooperation rate; under high temptation, the presence of strength individuals prevents the group from falling into total defection, helping ordinary individuals escape the defection dilemma and improve cooperation levels.

摘要

近年来,耦合双层网络在进化博弈论中发挥着越来越关键的作用。研究表明,这些网络能更准确地反映个体之间的现实世界关系。然而,目前的研究主要集中在双层网络内的单向影响。基于此,我们提出了一个强耦合双层网络合作进化模型。强势个体位于上层网络,影响下层普通个体的策略选择,反之亦然。蒙特卡洛模拟表明,强势个体能够有效提高群体整体合作水平。在低背叛诱惑下,群体保持较高的合作率;在高诱惑下,强势个体的存在防止群体陷入完全背叛,帮助普通个体摆脱背叛困境并提高合作水平。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ff3/11785339/e6a6d6796e31/pone.0317923.g001.jpg

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