Aims and scope

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.

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.