Evolutionary games on multilayer networks: a colloquium

By Zhen Wang, L. Wang, Attila Szolnoki, Matjaz Perc. European Physical Journal B : Condensed Matter Physics, 2015

732 citations recorded by the source corpus.

Networks form the backbone of many complex systems, ranging from the Internet to human societies. Accordingly, not only is the range of our interactions limited and thus best described and modeled by networks, it is also a fact that the networks that are an integral part of such models are often interdependent or even interconnected. Networks of networks or multilayer networks are therefore a more apt description of social systems. This colloquium is devoted to evolutionary games on multilayer networks, and in particular to the evolution of cooperation as one of the main pillars of modern human societies. We first give an overview of the most significant conceptual differences between single-layer and multilayer networks, and we provide basic definitions and a classification of the most commonly used terms. Subsequently, we review fascinating and counterintuitive evolutionary outcomes that emerge due to different types of interdependencies between otherwise independent populations. The focus is on coupling through the utilities of players, through the flow of information, as well as through the popularity of different strategies on different network layers. The colloquium highlights the importance of pattern formation and collective behavior for the promotion of cooperation under adverse conditions, as well as the synergies between network science and evolutionary game theory.

Subfields: Management Science and Operations Research, Sociology and Political Science, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/31651c1eb8ceba15c6dc9127487217372cab97b8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Science and Operations Research

In Sociology and Political Science

In Statistical and Nonlinear Physics

Citations in the corpus

Evolutionary dynamics of higher-order interactions in social networks (2020, background): “As such, it can be used in future research towards upgrades that add additional layers of reality in models of human cooperation, either by means of strategic complexity [9], or by means of more complex interaction networks [59].”
Statistical physics of vaccination (2016, background): “Not surprisingly, multilayer networks have recently been the subject of many novel frameworks to study various dynamical processes, such as epidemic spreading [216, 231, 372, 604], diffusion [342], voting [605], synchronization [606], and the evolution of cooperation in game-theoretical models [607,”
Wavelet Multiresolution Complex Network for Analyzing Multivariate Nonlinear Time Series (2017, methodology): “…network originates from graph theory, which is an abstract description of the complex system, consisting of nodes and the edges between the nodes [Wang et al., 2016; Boccaletti et al., 2014; Zou et al., 2015; Kim et al., 2013; Huang et al., 2014; Lu et al., 2013; Kenett et al., 2015; Lu & Chen,…”
A hybrid multi-stage stochastic programming-robust optimization model for maximizing the supply chain of a forest-based biomass power plant considering uncertainties (2016, methodology): “Barring technological breakthroughs, modeling based on game theory have been considered (for an introduction see Perc and Szolnoki (2010), Wang et al. (2015), Perc (2006, 2007)).”
Networks beyond pairwise interactions: structure and dynamics (2020, background): “[544] Zhen Wang, Lin Wang, Attila Szolnoki, and Matjaž Perc.”
Network science of biological systems at different scales: A review. (2017, background): “[21] Wang Z, Wang L, Szolnoki A, Perc M.”
Coupled disease–behavior dynamics on complex networks: A review (2015, background): “Subsequently, more properties of social networks have been extensively investigated, such as community structure (a kind of assortative structure where individuals are divided into groups such that the members within each group are mostly connected with each other) [26] , clusters [27] , and the rec”