In past years, adaptive networks have been discovered simultaneously in different fields as a universal framework for the study of self-organization phenomena. Understanding the mechanisms behind these phenomena is hoped to bring forward not only empirical disciplines such as biology, sociology, ecology, and economy, but also engineering disciplines seeking to employ controlled emergence in future technologies.
Self-Organization in Continuous Adaptive Networkspresents new analytical approaches, which combine tools from dynamical systems theory and statistical physics with tools from graph theory to address the principles behind adaptive self-organization. It is the first class of approaches that is applicable to continuous networks.
This book discusses the mechanisms behind three emergent phenomena that are prominently discussed in the context of biological and social sciences:
Self-Organization in Continuous Adaptive Networkscontains extended research papers. It can serve as both a review of recent results on adaptive self-organization and as a tutorial of new analytical methods. This publication is ideal for academic staff and master/research students in complexity and network sciences, in engineering, physics, and math.