Complex Systems And Networks

This elementary book provides some state-of-the-art research results on broad disciplinary sciences on complex networks. It presents an in-depth study with detailed description of dynamics, controls and applications of complex networks. The contents of this book can be summarized as follows. First, the dynamics of complex networks, for example, the cluster dynamic analysis by using kernel spectral methods, community detection algorithms in bipartite networks, epidemiological modeling with demographics and epidemic spreading on multi-layer networks, are studied. Second, the controls of complex networks are investigated including topics like distributed finite-time cooperative control of multi-agent systems by applying homogenous-degree and Lyapunov methods, composite finite-time containment control for disturbed second-order multi-agent systems, fractional-order observer design of multi-agent systems, chaos control and anticontrol of complex systems via Parrondos game and many more. Third, the applications of complex networks provide some applicable carriers, which show the importance of theories developed in complex networks. In particular, a general model for studying time evolution of transition networks, deflection routing in complex networks, recommender systems for social networks analysis and mining, strategy selection in networked evolutionary games, integration and methods in computational biology, are discussed in detail.

This book investigates how various scientific communities – e.g. legal scientists, political scientists, sociologists, mathematicians, and computer scientists – study law and public policies, which are portrayed here as complex systems. Today, research on law and public policies is rapidly developing at the international level, relying heavily on modeling that employs innovative methods for concrete implementation. Among the subject matter discussed, law as a network of evolving and interactive norms is now a prominent sphere of study. Similarly, public policies are now a topic in their own right, as policy can no longer be examined as a linear process; rather, its study should reflect the complexity of the networks of actors, norms and resources involved, as well as the uncertainty or weak predictability of their direct or indirect impacts. The book is divided into three maain parts: complexity faced by jurists, complexity in action and public policies, and complexity and networks. The main themes examined concern codification, governance, climate change, normative networks, health, water management, use-related conflicts, legal regime conflicts, and the use of indicators.

The modern world is complex beyond human understanding and control. The science of complex systems aims to find new ways of thinking about the many interconnected networks of interaction that defy traditional approaches. Thus far, research into networks has largely been restricted to pairwise relationships represented by links between two nodes. This volume marks a major extension of networks to multidimensional hypernetworks for modeling multi-element relationships, such as companies making up the stock market, the neighborhoods forming a city, people making up committees, divisions making up companies, computers making up the internet, men and machines making up armies, or robots working as teams. This volume makes an important contribution to the science of complex systems by: (i) extending network theory to include dynamic relationships between many elements; (ii) providing a mathematical theory able to integrate multilevel dynamics in a coherent way; (iii) providing a new methodological approach to analyze complex systems; and (iv) illustrating the theory with practical examples in the design, management and control of complex systems taken from many areas of application. Contents:IntroductionSets and RelationsHypergraphs and the Galois LatticeSimplicial Complexes and Q-AnalysisBackcloth and Traffic: Dynamics Constrained by TopologyHypernetworksMultilevel SystemsTime, Events, Prediction and ForecastingHypernetworks and DesignPolicy, Design, Planning and ScienceNotes and Reflections Readership: Academics: researchers, scientists, social scientists, complex systems scientists, economists, biologists; Industry: managers, planners, consultants, knowledge professionals, systems engineers, automation specialists, supply chain managers; Public services: Council Officers, city planners, transport planners, health professionals, welfare professionals. Key Features:A first book of its kind on 'hypernetworks', a term the author has coined to describe the mathematical structures he has worked on over the last 30 yearsIntroduces hypernetworks in the context of examples drawn from a wide range of fields, including design, planning, management, art, neural network, machine vision, robotics, traffic, road accidents, amongst othersThe emphasis of this volume is on useful and added-value applications. It will develop the necessary mathematics and assuming no pre-requisitesContains a myriad of illustrations to further understand the topics discussedReviews: “The mathematics is explicitly explained and no difficult theorems are included in this book in order to enable scientists, designers and policy makers to work together.” Zentralblatt MATH

Adding one and one makes two, usually. But sometimes things add up to more than the sum of their parts. This observation, now frequently expressed in the maxim “more is different”, is one of the characteristic features of complex systems and, in particular, complex networks. Along with their ubiquity in real world systems, the ability of networks to exhibit emergent dynamics, once they reach a certain size, has rendered them highly attractive targets for research. The resulting network hype has made the word “network” one of the most in uential buzzwords seen in almost every corner of science, from physics and biology to economy and social sciences. The theme of “more is different” appears in a different way in the present v- ume, from the viewpoint of what we call “adaptive networks.” Adaptive networks uniquely combine dynamics on a network with dynamical adaptive changes of the underlying network topology, and thus they link classes of mechanisms that were previously studied in isolation. Here adding one and one certainly does not make two, but gives rise to a number of new phenomena, including highly robust se- organization of topology and dynamics and other remarkably rich dynamical beh- iors.

This book reviews the synergism between various fields of research that are confronted with networks, such as genetic and metabolic networks, social networks, the Internet and ecological systems. In many cases, the interacting networks manifest so-called emergent properties that are not possessed by any of the individual components. Knowledge gained from the study of complex non-biological systems can be applied to the intricate braided relationships that govern cellular functions.

In this book for the first time two scientific fields - consensus formation and synchronization of communications - are presented together and examined through their interrelational aspects, of rapidly growing importance. Both fields have indeed attracted enormous research interest especially in relation to complex networks. In networks of dynamic systems (or agents), consensus means to reach an agreement regarding a certain quantity of interest that depends on the state of all dynamical systems (agents). Consensus problems have a long history in control theory and computer sciences, and form the foundation of the field of distributed computing. Synchronization, which defines correlated-in-time behavior between different processes and roots going back to Huygens to the least, is now a highly popular, exciting and rapidly developing topic, with applications ranging from biological networks to mathematical epidemiology, and from processing information in the brain to engineering of communications devices. The book reviews recent finding in both fields and describes novel approaches to consensus formation, where consensus is realized as an instance of the nonlinear dynamics paradigm of chaos synchronization. The chapters are written by world-known experts in both fields and cover topics ranging from fundaments to various applications of consensus and synchronization.

Big data, genomics, and quantitative approaches to network-based analysis are combining to advance the frontiers of medicine as never before. With contributions from leading experts, Network Medicine introduces this rapidly evolving field of research, which promises to revolutionize the diagnosis and treatment of human diseases.