Adaptive Dynamical Networks

TL;DR

This review explores adaptive dynamical networks, systems that change their structure based on their state, highlighting their applications, dynamical features, phenomena, and mathematical methods for analysis.

Contribution

It provides a comprehensive overview of adaptive dynamical networks, emphasizing their importance, properties, and the mathematical tools used to study them.

Findings

Adaptive networks exhibit complex dynamical phenomena.

Applications span neuroscience, epidemiology, and social systems.

Mathematical methods are crucial for understanding their behavior.

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.