TY - JOUR
T1 - Focus issue on recent advances in adaptive dynamical networks
AU - Yanchuk, Serhiy
AU - Andreas Martens, Erik
AU - Kuehn, Christian
AU - Kurths, Jürgen
N1 - Publisher Copyright:
© 2025 Author(s).
PY - 2025/10/1
Y1 - 2025/10/1
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/105017681264
U2 - 10.1063/5.0300039
DO - 10.1063/5.0300039
M3 - Review article
C2 - 41031928
AN - SCOPUS:105017681264
SN - 1054-1500
VL - 35
JO - Chaos
JF - Chaos
IS - 10
M1 - 100401
ER -