Complexity

Complexity is a Section of the journal Fractal and Fractional, which publishes advanced theoretical studies and practical applications on the topic of complex systems.

Complex systems are often composed of several autonomous entities, usually described by simple rules that interact between each other and with their environment, giving rise to a collective behavior. This behavior exhibits emerging dynamical phenomena, which are impossible to be inferred from the properties and behavior of the individual parts. Often, complex systems reveal self-organization, adaptability, emergence of new orders and structures, transition states, long-range correlations in the time–space domain, chaoticity, fractality, regularity, and memory effects.

The study of complex systems can adopt a variety tools, but often those are far from capturing the overall richness of the systems’ dynamics. Therefore, novel perspectives are possible by using mathematical tools that are common in distinct areas. Complex systems are frequent in nature and in human-related activities, including financial markets, social, transportation, telecommunication and power-grid networks, world and country economies, ecosystems, molecular dynamics, immunology, living organisms, computational systems, and celestial and continuum mechanics.

The primary aim of Complexity is the publication and dissemination of relevant theoretical, numerical and practical works with importance to the subject of complex systems. All fields of engineering, physics, economy, mathematics, and other disciplines dealing with complex systems are within the scope of the Section.

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• adaptability
• agent-based modeling
• analytical methods
• bifurcation theory
• bioinformatics
• cellular automata
• complex networks
• complexity measures
• chaos theory
• computational complexity
• computational methods
• criticality
• disordered systems
• emergent behavior
• evolution
• evolutionary computing
• fractals
• fractional calculus
• game theory
• information theory
• long-range correlations
• machine learning
• nonlinear dynamical systems
• numerical methods
• pattern formation
• power law
• randomness
• self-organization
• statistical mechanics
• symmetry breaking
• synchronization
• time series