Complexity and Self-Organization

Abstract

Complexity occurs when relevant interactions prevent the study of elements of a system in isolation. These interactions between elements may lead to the self-organization of the system. In computational intelligence, complexity and self-organization have been studied and exploited with different purposes. This Research Topic aims to bring together novel research into a coherent collection, spanning from theory and methods to simulations and applications. Computational measures of complexity and self-organization have been proposed and applied to study a broad range of phenomena. Methodologies for facing complexity and harnessing self-organization have been used to design and build a variety of systems. Computer simulations have been tools which enabled us to study complexity and self-organization, from cellular automata and artificial neural networks to multi-agent systems and computational social science. The applications of these approaches have been vast.Considering that complexity and self-organization are very broad themes, this Research Topic focusses only on the aspects related to computational intelligence. These include:• Formal definitions of complexity and self-organization• Coordination, cooperation, and collective decision-making• Algorithms• Adaptability• Robustness• Simulations• Robotics• Methodologies• ApplicationsThis Research Topic will welcome submissions of all article types listed here.