Modeling complex systems with adaptive networks

Hiroki Sayama*, Irene Pestov, Jeffrey Schmidt, Benjamin James Bush, Chun Wong, Junichi Yamanoi, Thilo Gross

*この研究の対応する著者

研究成果: Article査読

101 被引用数 (Scopus)

抄録

Adaptive networks are a novel class of dynamical networks whose topologies and states coevolve. Many real-world complex systems can be modeled as adaptive networks, including social networks, transportation networks, neural networks and biological networks. In this paper, we introduce fundamental concepts and unique properties of adaptive networks through a brief, non-comprehensive review of recent literature on mathematical/computational modeling and analysis of such networks. We also report our recent work on several applications of computational adaptive network modeling and analysis to real-world problems, including temporal development of search and rescue operational networks, automated rule discovery from empirical network evolution data, and cultural integration in corporate merger.

本文言語English
ページ(範囲)1645-1664
ページ数20
ジャーナルComputers and Mathematics with Applications
65
10
DOI
出版ステータスPublished - 2013
外部発表はい

ASJC Scopus subject areas

  • モデリングとシミュレーション
  • 計算理論と計算数学
  • 計算数学

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