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Adaptive dynamical networks

  • Humboldt-Universität zu Berlin
  • Technische Universität Berlin
  • Helmholtz Institute for Functional Marine Biodiversity at the University of Oldenburg (HIFMB)
  • Universität Oldenburg
  • Centre for Polar and Marine Research
  • Complexity Science Hub Vienna
  • Potsdam Institute for Climate Impact Research (PIK)–Member of the Leibniz Association

Research output: Contribution to journalReview articlepeer-review

93 Scopus citations

Abstract

It is a fundamental challenge to understand how the function of a network is related to its structural organization. Adaptive dynamical networks represent a broad class of systems that can change their connectivity over time depending on their dynamical state. The most important feature of such systems is that their function depends on their structure and vice versa. While the properties of static networks have been extensively investigated in the past, the study of adaptive networks is much more challenging. Moreover, adaptive dynamical networks are of tremendous importance for various application fields, in particular, for the models for neuronal synaptic plasticity, adaptive networks in chemical, epidemic, biological, transport, and social systems, to name a few. In this review, we provide a detailed description of adaptive dynamical networks, show their applications in various areas of research, highlight their dynamical features and describe the arising dynamical phenomena, and give an overview of the available mathematical methods developed for understanding adaptive dynamical networks.

Original languageEnglish
Pages (from-to)1-59
Number of pages59
JournalPhysics Reports
Volume1031
DOIs
StatePublished - 10 Aug 2023

Keywords

  • Adaptation
  • Co-evolutionary
  • Complexity
  • Cooperation
  • Dynamics
  • Event-based adaptation
  • Mean-field
  • Multiscale
  • Networks
  • Neuronal plasticity
  • Opinion formation
  • Rewiring

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