This book offers a holistic framework to study behavior and evolutionary dynamics in large-scale, decentralized, and heterogeneous crowd networks. In the emerging crowd cyber-ecosystems, millions of deeply connected individuals, smart devices, government agencies, and enterprises actively interact with each other and influence each other’s decisions. It is crucial to understand such intelligent entities’ behaviors and to study their strategic interactions in order to provide important guidelines on the design of reliable networks capable of predicting and preventing detrimental events with negative impacts on our society and economy. This book reviews the fundamental methodologies to study user interactions and evolutionary dynamics in crowd networks and discusses recent advances in this emerging interdisciplinary research field. Using information diffusion over social networks as an example, it presents a thorough investigation of the impact of user behavior on the network evolution process and demonstrates how this can help improve network performance. Intended for graduate students and researchers from various disciplines, including but not limited to, data science, networking, signal processing, complex systems, and economics, the book encourages researchers in related research fields to explore the many untouched areas in this domain, and ultimately to design crowd networks with efficient, effective, and reliable services.

Until recently, most network design techniques employed a bottom-up approach with lower protocol layer mechanisms affecting the development of higher ones. This approach, however, has not yielded fascinating results in the case of wireless distributed networks. Addressing the emerging aspects of modern network analysis and design, Evolutionary Dyna

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This SpringerBrief brings order to the wealth of research studies that contribute to shape our understanding of on-line social networks (OSNs) lurking phenomena. This brief also drives the development of computational approaches that can be effectively applied to answer questions related to lurking behaviors, as well as to the engagement of lurkers in OSNs. All large-scale online social networks (OSNs) are characterized by a participation inequality principle, i.e., the crowd of an OSN does not actively contribute, rather it takes on a silent role. Silent users are also referred to as lurkers, since they gain benefit from others' information without significantly giving back to the community. Nevertheless, lurkers acquire knowledge from the OSN, therefore a major goal is to encourage them to more actively participate. Lurking behavior analysis has been long studied in social science and human-computer interaction fields, but it has also matured over the last few years in social network analysis and mining. While the main target audience corresponds to computer, network, and web data scientists, this brief might also help increase the visibility of the topic by bridging different closely related research fields. Practitioners, researchers and students interested in social networks, web search, data mining, computational social science and human-computer interaction will also find this brief useful research material .

Dancing humanoids, robotic art installations, and music generated by mathematically precise methods are no longer science fiction; in fact they are the subject of this book. This first-of-its-kind anthology assembles technical research that makes such creations possible. In order to mechanize something as enigmatic and personal as dance, researchers must delve deeply into two distinct academic disciplines: control theory and art. Broadly, this research uses techniques from the world of art to inspire methods in control, enables artistic endeavours using advanced control theory and aids in the analysis of art using metrics devised by a systems theoretic approach. To ensure that artistic influences are well represented, the individual chapters are focused so that they relate their contribution to the arts meaningfully and explicitly. Specially composed introductions set up the contributions either in terms of inspiration by artistic principles or their contribution to the arts through new analysis tools. To facilitate this, the majority of the chapters are authored jointly by experts in control theory and by artists, including dancers, choreographers, puppeteers and painters. Connections between controls and art then permeate the text so that these important relationships play a central role in the book. Controls and Art surveys current projects in this area—including a disco dancing robot, a reactive museum exhibit and otherworldly music—and illuminates open problems and topics for research in this emerging interdisciplinary field. It will draw attention both from experts in robotics and control interested in developing the artistic side of their creations and from academics studying dance, theater, music and the visual arts with an interest in avant-garde means of production.

This book presents an introduction to Evolutionary Game Theory (EGT) which is an emerging field in the area of complex systems attracting the attention of researchers from disparate scientific communities. EGT allows one to represent and study several complex phenomena, such as the emergence of cooperation in social systems, the role of conformity in shaping the equilibrium of a population, and the dynamics in biological and ecological systems.Since EGT models belong to the area of complex systems, statistical physics constitutes a fundamental ingredient for investigating their behavior. At the same time, the complexity of some EGT models, such as those realized by means of agent-based methods, often require the implementation of numerical simulations. Therefore, beyond providing an introduction to EGT, this book gives a brief overview of the main statistical physics tools (such as phase transitions and the Ising model) and computational strategies for simulating evolutionary games (such as Monte Carlo algorithms on lattices). This book will appeal to students and researchers in this burgeoning field of complex systems.

The scientific study of networks - computer, social, and biological - has received an enormous amount of interest in recent years. However, the network approach has been applied to the field of animal behaviour relatively late compared to many other biological disciplines. Understanding social network structure is of great importance for biologists since the structural characteristics of any network will affect its constituent members and influence a range of diverse behaviours. These include finding and choosing a sexual partner, developing and maintaining cooperative relationships, and engaging in foraging and anti-predator behavior. This novel text provides an overview of the insights that network analysis has provided into major biological processes, and how it has enhanced our understanding of the social organisation of several important taxonomic groups. It brings together researchers from a wide range of disciplines with the aim of providing both an overview of the power of the network approach for understanding patterns and process in animal populations, as well as outlining how current methodological constraints and challenges can be overcome. Animal Social Networks is principally aimed at graduate level students and researchers in the fields of ecology, zoology, animal behaviour, and evolutionary biology but will also be of interest to social scientists.