Complexity

The purpose of Complexity is to report important advances in the scientific study of complex systems. Complex systems are characterized by interactions between their components that produce new information — present in neither the initial nor boundary conditions — which limit their predictability. Given the amount of information processing required to study complexity, the use of computers has been central to complex systems research.

This Open Access journal publishes high-quality original research, as well as rigorous review articles, across a broad range of disciplines. Studies can have a theoretical, methodological, or practical focus. However, submissions must always provide a significant contribution to complex systems.

(topics of interest)

Concepts relevant to Complexity include:

Adaptability, robustness, and resilience
Complex networks
Criticality
Evolution and emergent behaviour
Nonlinear dynamics
Pattern formation
Self-organization

Methods used within the scientific study of complex systems frequently include:

Agent-based modelling
Analytical methods
Cellular automata
Computational methods
Data science
Game theory
Machine learning
Statistical mechanics

Applications of complex systems may be related to the following disciplines, among others:

Computational social science
Digital epidemiology
Ecology
Economics
Engineering
Socio-technical systems
Statistical linguistics
Systems biology
Urban systems

Work that considers the above methods or applications, but which is not applied to the study of complex systems will be considered out of scope. For the avoidance of doubt, ‘complex’ in the context of this journal should not be considered merely as a synonym for difficult or complicated.