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SCIENTIA SINICA Informationis, Volume 50 , Issue 11 : 1714(2020) https://doi.org/10.1360/SSI-2020-0087

Spreading dynamics on complex dynamical networks

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  • ReceivedApr 9, 2020
  • AcceptedMay 21, 2020
  • PublishedOct 20, 2020

Abstract

With the development of network science, spreading dynamics on networks have attracted intensive research interests in a wide variety of areas, such as control theory, game theory, system science, artificial intelligence, social science, economics, biology, psychology, physics, math, and computer science. Network structure plays a key role in spreading dynamics, although spreading dynamics differ from one another. In real networked systems, the neighborhoods of individuals evolve with time. It is thus necessary to consider the coupling between spreading dynamics and network dynamics. Nowadays the research on spreading dynamics on dynamical networks usually use Monte Carlo simulation rather than theoretical methods. So, we propose a stochastic linking dynamic in this paper. It is proved to be a reversible Markov chain, which facilitates the analytical investigation of spreading dynamics on dynamical networks. With this method, we study three spreading dynamics: the evolution of cooperation, the spread of epidemics, and the evolution of vaccination behavior. Furthermore, we show the similarities and differences between evolutionary game dynamics and epidemic spreading dynamics. Our method could provide a universal framework to study spreading dynamics on complex dynamical networks.


Funded by

国家自然科学基金(61751301,61533001,11971405,61703082)

中央高校基本科研业务费(20720180005,N2004004)


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