2017/09/30 by Malte Schröder, Jan Nagler, Marc Timme +1
Decision Sciences · Mathematics · Physics and Astronomy · #Complex Network Analysis Techniques #Complex network #Computer science #Game Theory and Applications #Mathematical optimization #Mathematics #Opinion Dynamics and Social Influence #Percolation (cognitive psychology) #Percolation theory #Physics #Process (computing) #Ranging #Scale (ratio) #Topology (electrical circuits) #cond-mat.dis-nn #physics.soc-ph
paper · pdf · doi:10.1103/physrevlett.120.248302
published as Phys. Rev. Lett. 120, 248302 (2018) · 6 pages, 5 figures and an additional 23 pages, 10 figures appendix/supplement. See also ancillary files for data
arxiv created 2018/05/08 · openalex publication_date 2018/06/14 · arxiv updated 2018/06/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
The emergence of large-scale connectivity underlies the proper functioning of many networked systems, ranging from social networks and technological infrastructure to global trade networks. Percolation theory characterizes network formation following stochastic local rules, while optimization models of network formation assume a single controlling authority or one global objective function. In socioeconomic networks, however, network formation is often driven by individual, locally optimal decisions. How such decisions impact connectivity is only poorly understood to date. Here, we study how large-scale connectivity emerges from decisions made by rational agents that individually minimize costs for satisfying their demand. We establish that the solution of the resulting nonlinear optimization model is exactly given by the final state of a local percolation process. This allows us to systematically analyze how locally optimal decisions on the microlevel define the structure of networks on the macroscopic scale.