Focus issue on recent advances in adaptive dynamical networks
(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.
(Less)
- author
- Yanchuk, Serhiy
; Andreas Martens, Erik
LU
; Kuehn, Christian
and Kurths, Jürgen
- organization
- publishing date
- 2025-10
- 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}},
}