Title
Modeling complex systems with adaptive networks.
Abstract
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.
Year
DOI
Venue
2013
10.1016/j.camwa.2012.12.005
Computers & Mathematics with Applications
Keywords
DocType
Volume
Adaptive networks,Complex systems,Complex networks,State-topology coevolution,Dynamics,Generative network automata
Journal
65
Issue
ISSN
Citations 
10
0898-1221
16
PageRank 
References 
Authors
0.80
17
7
Name
Order
Citations
PageRank
Hiroki Sayama131949.14
Irene Pestov2202.01
Jeffrey Schmidt3160.80
Benjamin James Bush4181.61
Chun Wong5191.23
Junichi Yamanoi6221.57
Thilo Gross75211.51