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.
works as
journal
containing
Scalable Distributed Decision-Making and Coordination in Large and Complex Systems: Methods, Techniques, and Models (2020) — Marin Lujak, Stefano Giordani, Andrea Omicini, Sascha Ossowski