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.

Special Issue on Complex Systems in Aesthetics, Creativity and Arts
提出日: 2024-10-18

Description

One of the main - possibly unattainable - challenges of computational arts is to build algorithms that evaluate properties such as novelty, creativity, and aesthetic properties of artistic artifacts or representations. Approaches in this regard have often been based on information-theoretic ideas. For example, ideas relating mathematical notions of form and balance to beauty date to antiquity. In the 20th century, attempts were made to develop aesthetic measures based on the ideas of balance between order and complexity. In recent years, these ideas have been formalized into the idea that aesthetic engagement occurs when work is on the "edge of chaos," between excessive order and excessive disorder, formalizing it through notions such as the Gini coefficient and Shannon entropy, and links between cognitive theories of Bayesian brain and free energy minimization with aesthetic theories. These ideas have been used both to understand human behavior and to build creative systems.

The use of artificial intelligence and complex systems for the development of artistic systems is an exciting and relevant area of research. In recent years, there has been an enormous interest in the application of these techniques in fields such as visual art and music generation, analysis and performance, sound synthesis, architecture, video, poetry, design, game content generation, and other creative endeavors.

This Special Issue invites original research and review articles which will focus on both the use of complexity ideas and artificial intelligence methods to analyze and evaluate aesthetic properties and to drive systems that generate aesthetically appealing artifacts, including: music, sound, images, animation, design, architectural plans, choreography, poetry, text, jokes, etc.

Potential topics include but are not limited to the following:

    Computational aesthetics
    Formalising the ideas of aesthetics using ideas from entropy and information theory
    Computational creativity
    Artificial Intelligence in art, design, architecture, music, and games
    Information Theory in art, design, architecture, music, and games
    Complex systems in art, music ,and design
    Evolutionary art and music
    Deep ;learning models to art and video creation
    Artificial life in arts
    Swarm art
    Pattern recognition and aesthetics
    Cellular automata in architecture
    Generative AI

Editors

Lead Editor

Juan Romero1
1University of A Coruña, A Coruña, Spain

Guest Editors

Penousal Machado1 | Colin Johnson2
1University of Coimbra, Coimbra, Portugal
2University of Nottingham, Nottingham, UK