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.