The impact of conditional coupling based on environment comparison between interdependent networks on the evolution of cooperation

IF 5.3 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Chaos Solitons & Fractals Pub Date : 2024-08-24 DOI:10.1016/j.chaos.2024.115427
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Abstract

The coupling between interdependent networks is a crucial factor affecting the evolution of cooperation. Actually, not all nodes in different sub-networks of the interdependent network can establish a one-to-one corresponding coupling relationship, and whether the connection between corresponding nodes can be built is often related to the local environment and global environment where the individual is located. Therefore, we explore how the conditional coupling between interdependent networks based on the comparisons of local and global environments affects the spread of cooperative behavior. We consider two types of conditional coupling modes: static coupling and dynamic coupling. The classic prisoner’s dilemma is chosen as the fundamental game model. The numerical simulation results on the interdependent network constructed by square lattices show that conditional coupling based on environmental comparison favors the propagation of cooperation, regardless of the type of conditional coupling. And the promotion level of cooperation is proportional to the coupling strength. Moreover, we further perform the simulation experiments on the interdependent networks composed of ER (Erdös–Rényi) random networks. Our explorations may be helpful for understanding the survival and maintenance of cooperation in the interconnected and interrelated systems.

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基于相互依存网络间环境比较的条件耦合对合作演化的影响
相互依存网络之间的耦合是影响合作演化的关键因素。实际上,相互依赖网络中不同子网络的节点并非都能建立一对一的对应耦合关系,对应节点之间能否建立联系往往与个体所处的局部环境和全局环境有关。因此,我们探讨了基于本地环境和全局环境比较的相互依赖网络之间的条件耦合如何影响合作行为的传播。我们考虑了两种条件耦合模式:静态耦合和动态耦合。我们选择经典的囚徒困境作为基本博弈模型。在方格构建的相互依存网络上的数值模拟结果表明,无论哪种条件耦合,基于环境比较的条件耦合都有利于合作的传播。而合作的促进程度与耦合强度成正比。此外,我们还进一步对由 ER(Erdös-Rényi)随机网络组成的相互依存网络进行了模拟实验。我们的探索可能有助于理解相互关联系统中合作的生存与维持。
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来源期刊
Chaos Solitons & Fractals
Chaos Solitons & Fractals 物理-数学跨学科应用
CiteScore
13.20
自引率
10.30%
发文量
1087
审稿时长
9 months
期刊介绍: Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.
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