title: An evolutionary game approach for determination of the structural conflicts in signed networks.
abstract: Social or biochemical networks can often divide into two opposite alliances in response to structural conflicts between positive (friendly, activating) and negative (hostile, inhibiting) interactions. Yet, the underlying dynamics on how the opposite alliances are spontaneously formed to minimize the structural conflicts is still unclear. Here, we demonstrate that evolutionary game dynamics provides a felicitous possible tool to characterize the evolution and formation of alliances in signed networks. Indeed, an evolutionary game dynamics on signed networks is proposed such that each node can adaptively adjust its choice of alliances to maximize its own fitness, which yet leads to a minimization of the structural conflicts in the entire network. Numerical experiments show that the evolutionary game approach is universally efficient in quality and speed to find optimal solutions for all undirected or directed, unweighted or weighted signed networks. Moreover, the evolutionary game approach is inherently distributed. These characteristics thus suggest the evolutionary game dynamic approach as a feasible and effective tool for determining the structural conflicts in large-scale on-line signed networks.
authors.affiliation: College of Electrical and Information Engineering, Hunan University, Changsha 410082, China.
authors.forename: Shaolin
authors.initials: S
authors.lastname: Tan
authors.affiliation: Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.
authors.forename: Jinhu
authors.initials: J
authors.lastname: Lü
mesh_terms: D000818:Animals; D005075:Biological Evolution; D004926:Escherichia coli / Q000378:metabolism; D005716:Game Theory; D006801:Humans; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D060756:Social Networking; D035503:Sociobiology; D015003:Yeasts / Q000378:metabolism