Editorial Comment on the Special Issue of "Information in Dynamical Systems and Complex Systems"

TL;DR

This special issue highlights recent advances at the intersection of information theory and dynamical systems, focusing on information flow, causality, modeling, and statistical testing in complex systems.

Contribution

It compiles diverse contributions offering new theoretical insights, methods, and rigorous analyses of information dynamics in complex and stochastic systems.

Findings

Theoretical characterization of information flow and causality.

Methods for inference and identification of system coupling.

Exact statistical testing of information-theoretic quantities.

Abstract

This special issue collects contributions from the participants of the "Information in Dynamical Systems and Complex Systems" workshop, which cover a wide range of important problems and new approaches that lie in the intersection of information theory and dynamical systems. The contributions include theoretical characterization and understanding of the different types of information flow and causality in general stochastic processes, inference and identification of coupling structure and parameters of system dynamics, rigorous coarse-grain modeling of network dynamical systems, and exact statistical testing of fundamental information-theoretic quantities such as the mutual information. The collective efforts reported herein reflect a modern perspective of the intimate connection between dynamical systems and information flow, leading to the promise of better understanding and modeling of natural complex systems and better/optimal design of engineering systems.