计算机科学
相互依存
编码
相互依存的网络
复杂系统
生命系统
复杂网络
数据科学
分布式计算
网络科学
理论计算机科学
人工智能
生物
万维网
生物化学
政治学
法学
基因
作者
Alberto Aleta,Yamir Moreno
标识
DOI:10.1146/annurev-conmatphys-031218-013259
摘要
Complex systems are characterized by many interacting units that give rise to emergent behavior. A particularly advantageous way to study these systems is through the analysis of the networks that encode the interactions among the system constituents. During the past two decades, network science has provided many insights in natural, social, biological, and technological systems. However, real systems are often interconnected, with many interdependencies that are not properly captured by single-layer networks. To account for this source of complexity, a more general framework, in which different networks evolve or interact with each other, is needed. These are known as multilayer networks. Here, we provide an overview of the basic methodology used to describe multilayer systems as well as of some representative dynamical processes that take place on top of them. We round off the review with a summary of several applications in diverse fields of science.
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