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Focus issue on recent advances in adaptive dynamical networks

Yanchuk, Serhiy ; Andreas Martens, Erik LU orcid ; Kuehn, Christian and Kurths, Jürgen (2025) In Chaos 35(10).
Abstract

Adaptive dynamical networks (ADNs) describe systems in which the states of the network nodes and the network structure itself co-evolve over time. This interplay of two coupled dynamical processes underlies a wide range of natural and technological phenomena, such as neural plasticity, learning, and opinion formation. The inherently co-evolutionary nature of ADNs poses significant challenges to mathematical theory and modeling, driving strong interest and rapid advances in recent years. This Focus Issue presents 25 research articles highlighting recent developments in the field, including new analytical and computational techniques, the discovery of novel dynamical phenomena in ADNs, and diverse applications of ADNs in neuroscience,... (More)

Adaptive dynamical networks (ADNs) describe systems in which the states of the network nodes and the network structure itself co-evolve over time. This interplay of two coupled dynamical processes underlies a wide range of natural and technological phenomena, such as neural plasticity, learning, and opinion formation. The inherently co-evolutionary nature of ADNs poses significant challenges to mathematical theory and modeling, driving strong interest and rapid advances in recent years. This Focus Issue presents 25 research articles highlighting recent developments in the field, including new analytical and computational techniques, the discovery of novel dynamical phenomena in ADNs, and diverse applications of ADNs in neuroscience, Earth science, biology, social sciences, machine learning and control.

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Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Chaos
volume
35
issue
10
article number
100401
publisher
American Institute of Physics (AIP)
external identifiers
  • pmid:41031928
  • scopus:105017681264
ISSN
1054-1500
DOI
10.1063/5.0300039
language
English
LU publication?
yes
id
7c42515d-38c2-4c61-b2bc-5f93083ac08d
date added to LUP
2025-11-25 14:45:50
date last changed
2025-11-26 03:33:05
@article{7c42515d-38c2-4c61-b2bc-5f93083ac08d,
  abstract     = {{<p>Adaptive dynamical networks (ADNs) describe systems in which the states of the network nodes and the network structure itself co-evolve over time. This interplay of two coupled dynamical processes underlies a wide range of natural and technological phenomena, such as neural plasticity, learning, and opinion formation. The inherently co-evolutionary nature of ADNs poses significant challenges to mathematical theory and modeling, driving strong interest and rapid advances in recent years. This Focus Issue presents 25 research articles highlighting recent developments in the field, including new analytical and computational techniques, the discovery of novel dynamical phenomena in ADNs, and diverse applications of ADNs in neuroscience, Earth science, biology, social sciences, machine learning and control.</p>}},
  author       = {{Yanchuk, Serhiy and Andreas Martens, Erik and Kuehn, Christian and Kurths, Jürgen}},
  issn         = {{1054-1500}},
  language     = {{eng}},
  number       = {{10}},
  publisher    = {{American Institute of Physics (AIP)}},
  series       = {{Chaos}},
  title        = {{Focus issue on recent advances in adaptive dynamical networks}},
  url          = {{http://dx.doi.org/10.1063/5.0300039}},
  doi          = {{10.1063/5.0300039}},
  volume       = {{35}},
  year         = {{2025}},
}