Spreading Control in Two-Layer Multiplex Networks

Jaquez, Roberto Bernal; Ramos, Luis Angel Alarcón; Schaum, Alexander

doi:10.3390/e22101157

Cited by 6 publications

(4 citation statements)

References 48 publications

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“…Indeed, the multilayer network models are able to account for the variety of different social contexts an individual may be involved in, and are thus crucial for an in-depth understanding of human cooperation than the single-layer network models. 19,20 . Huang conducted a study on the impact of external forcing on evolutionary games within complex networks 21 .…”

Section: Introductionmentioning

confidence: 99%

Impact of Discrepant Accumulations Strategy on Collective Cooperation in Multilayer Networks

He,

Ge,

Yang

et al. 2024

Preprint

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Understanding large-scale cooperation among related individuals has been one of the largest challenges. Since humans are in multiple social networks, the theoretical framework of multilayer networks is perfectly suited for studying this fascinating aspect of our biology. To that effect, we here study the cooperation in evolutionary game on interdependent networks. Importantly, a part of players are set to adopt Discrepant Accumulations Strategy. Players employing this mechanism not only use their payoffs in the multilayer network as the basis for the updating process as in previous experiments, but also take into account the similarities and differences in strategies across different layers. Monte Carlo simulations demonstrate that considering the similarities and differences in strategies across layers when calculating fitness can significantly enhance the cooperation level in the system. By examining the behavior of different pairing mode within cooperators and defectors, the equilibrium state can be attributed to the evolution of correlated pairing mode between interdependent networks. Our results provide a theoretical analysis of the group cooperation induced by the Discrepant Accumulations Strategy. And we also discuss potential implications of these findings for future human experiments concerning the cooperation on multilayer networks.

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Section: Introductionmentioning

confidence: 99%

Impact of Discrepant Accumulations Strategy on Collective Cooperation in Multilayer Networks

He,

Ge,

Yang

et al. 2024

Preprint

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“…With the progress of network science, this concept is of concern again to study the online communities [ 24 ], the internet [ 25 ], the citation networks [ 26 ], the trade networks [ 27 ], and other social interactions [ 28 , 29 ]. Meanwhile, the multilayer network models somehow provide a framework to study the human cooperation and social dynamics that is closer to reality than the single-layer network models [ 30 , 31 ], where numerous studies pay attention to some specific social phenomenon that may influence cooperation in the human population. Huang et al studied the effects of external forcing on evolutionary games in complex networks [ 32 ], finding that the mechanism of external forcing on the evolutionary game is a strong promoter of cooperation even under a severe temptation condition.…”

Section: Introductionmentioning

confidence: 99%

Prisoner’s Dilemma Game with Cooperation-Defection Dominance Strategies on Correlational Multilayer Networks

Zhao

Feng

2022

Entropy

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As multilayer networks are widely applied in modern society, numerous studies have shown the impact of a multilayer network structure and the network nature on the proportion of cooperators in the network. In this paper, we use Barabási–Albert scale-free networks (BA) and Watts and Strogatz networks (WS) to build a multilayer network structure, and we propose a new strategy-updating rule called “cooperation-defection dominance”, which can be likened to dominant and recessive traits in biogenetics. With the newly constructed multilayer network structure and the strategy-updating rules, based on the simulation results, we find that in the BA-BA network, the cooperation dominance strategy can make the networks with different rs show a cooperative trend, while the defection dominance strategy only has an obvious effect on the network cooperation with a larger r. When the BA network is connected to the WS network, we find that the effect of strategy on the proportion of cooperators in the network decreases, and the main influencing factor is the structure of the network. In the three-layer network, the cooperation dominance strategy has a greater impact on the BA network, and the proportion of the cooperators is enhanced more than under the natural evolution strategy, but the promotion effect is still smaller than that of the two-layer BA network because of the WS network. Under the defection dominance strategy, the WS layer appears different from the first two strategies, and we conclude through simulation that when the payoff parameter is at the middle level, its cooperator proportion will be suppressed, and we deduce that the proportion of cooperators and defectors, as well as the payoff, play an important role.

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“…These networks are an important interdisciplinary research field that has attracted the interest of many scholars. In recent years, many new advances have been made in the research of complex networks, such as the spread and stability of complex networks [5,6], the synchronization and consensus of multi-layer complex networks [7][8][9][10][11][12][13][14][15], diffusion in multi-layer networks [16][17][18][19][20], and the modeling and robustness of multi-layer complex networks [21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Synchronizability of Multi-Layer-Coupled Star-Composed Networks

Gao¹,

Zhu

et al. 2021

Symmetry

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In this paper, several multi-layer-coupled star-composed networks with similar symmetrical structures are defined by using the theory of graph operation. The supra-Laplacian matrix of the corresponding multi-layer networks is obtained according to the master stability equation (MSF). Two important indexes that reflect the synchronizability of these kinds of networks are derived in the case of bounded and unbounded synchronized regions. The relationships among the synchronizability, the number of layers, the length of the paths, the branchings, and the interlayer and intralayer coupling strengths in the two cases are studied. At the same time, the simulation experiments are carried out with the MATLAB software, and the simulated images of the two symmetrical structure networks’ synchronizability are compared. Finally, the factors affecting the synchronizability of multi-layer-coupled star-composed networks are found. On this basis, optimization schemes are given to improve the synchronizability of multi-layer-coupled star-composed networks and the influences of the number of central nodes on the networks’ synchronizability are further studied.

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Spreading Control in Two-Layer Multiplex Networks

Cited by 6 publications

References 48 publications

Impact of Discrepant Accumulations Strategy on Collective Cooperation in Multilayer Networks

Impact of Discrepant Accumulations Strategy on Collective Cooperation in Multilayer Networks

Prisoner’s Dilemma Game with Cooperation-Defection Dominance Strategies on Correlational Multilayer Networks

Synchronizability of Multi-Layer-Coupled Star-Composed Networks

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