2004/08/03 by Venkat Venkatasubramanian, Venkatasubramanian, Venkat, Dimitris N. Politis +3
Mathematics · Physics and Astronomy · #Adaptation and Self-Organizing Systems (nlin.AO) #Complex Network Analysis Techniques #FOS: Biological sciences #FOS: Computer and information sciences #FOS: Physical sciences #Graph theory and applications #Information Theory (cs.IT) #Opinion Dynamics and Social Influence #Quantitative Methods (q-bio.QM) #Statistical Mechanics (cond-mat.stat-mech)
paper · pdf · doi:10.48550/arxiv.nlin/0408007
openalex publication_date 2004/08/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We present a general holistic theory for the organization of complex networks, both human-engineered and naturally-evolved. Introducing concepts of value of interactions and satisfaction as generic network performance measures, we show that the underlying organizing principle is to meet an overall performance target for wide-ranging operating or environmental conditions. This design or survival requirement of reliable performance under uncertainty leads, via the maximum entropy principle, to the emergence of a power law vertex degree distribution. The theory also predicts exponential or Poisson degree distributions depending on network redundancy, thus explaining all three regimes as different manifestations of a common underlying phenomenon within a unified theoretical framework.