## Self-Organization in Continuous Adaptive NetworksIn 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: * synchronization * spontaneous diversification * self-organized criticality. 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. |

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Self-Organization in Continuous Adaptive Networks Dr. Anne-Ly Do,Dr. Thilo Gross Limited preview - 2012 |

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active phase adaptive network models adaptive SOC adjacency matrix agents application approaches behavior bidirectional bifurcation cellular automata Chapter codimension collaborations connected consider continuous network cooperation defined degree distribution denote depends discrete network Dq,S dynamical systems emergence evolved networks example Figure giant component global phase graph G graph theory graphical notation inhomogeneous phase interaction Jacobi’s signature criterion Jacobian Kuramoto model Lett link ij link weights low-T phase macroscopic matrix mean degree measure Cij neuron nodes measuring Oi observed Ohom opposing processes order parameter parameter space pattern payoff phase boundary phase is homogeneous phase locked phase oscillators phase transition Phys properties random graphs recipe reveals Section self-organized criticality SOC models space of topological stability conditions statistical physics structure subgraphs threshold topological configuration topological dynamics topological evolution topological stability topological update rule topological variables total investment tuning unidirectional links zero row sum