This book explores recent developments in theoretical research and data analysis of real-world complex systems, organized in three parts, namely Entropy, information, and complexity functions Multistability, oscillations, and rhythmic synchronization Diffusions, rotation, and convection in fluids The collection of works devoted to the memory of Professor Valentin Afraimovich provides a deep insight into the recent developments in complexity science by introducing new concepts, methods, and applications in nonlinear dynamical systems covering physical problems and mathematical modelling relevant to economics, genetics, engineering vibrations, as well as classic problems in physics, fluid and climate dynamics, and urban dynamics. The book facilitates a better understanding of the mechanisms and phenomena in nonlinear dynamics and develops the corresponding mathematical theory to apply nonlinear design to practical engineering. It can be read by mathematicians, physicists, complex systems scientists, IT specialists, civil engineers, data scientists, and urban planners.

a theoretical and practical critique of the methods (net energy analysis and Energy Return On Investment - EROI) so far proposed to assess the quality of energy sources a critical appraisal of existing energy statistics explaining their shortcomings presents an innovative approach capable of generating flexible protocols of energy accounting (to be tailored on the specificity of different situations) across scales

This book, edited and authored by a closely collaborating network of social scientists and psychologists, recasts typical research topics in these fields into the language of nonlinear, dynamic and complex systems. The aim is to provide scientists with different backgrounds - physics, applied mathematics and computer sciences - with the opportunity to apply the tools of their trade to an altogether new range of possible applications. At the same time, this book will serve as a first reference for a new generation of social scientists and psychologists wishing to familiarize themselves with the new methodology and the "thinking in complexity".

This anthology contains selected papers from the 'Science as Culture' conference held at Lake Como, and Pavia University Italy, 15-19 September 1999. The conference, attended by about 220 individuals from thirty countries, was a joint venture of the International History, Philosophy and Science Teaching Group (its fifth conference) and the History of Physics and Physics Teaching Division of the European Physical Society (its eighth conference). The magnificient Villa Olmo, on the lakeshore, provided a memorable location for the presentors of the 160 papers and the audience that discussed them. The conference was part of local celebrations of the bicentenary of Alessandro Volta's creation of the battery in 1799. Volta was born in Como in 1745, and for forty years from 1778 he was professor of experimental physics at Pavia University. The conference was fortunate to have had the generous financial support of the Italian government's Volta Bicentenary Fund, Lombardy region, Pavia University, Italian Research Council, and Kluwer Academic Publishers. The papers included here, have or will be, published in the journal Science & Education, the inaugural volume (1992) of which was a landmark in the history of science education publication, because it was the first journal in the field devoted to contributions from historical, philosophical and sociological scholarship. Clearly these 'foundational' disciplines inform numerous theoretical, curricular and pedagogical debates in science education. Contemporary Concerns The reseach promoted by the International and European Groups, and by the journal, is central to science education programmes in most areas of the world.

This first part presents chapters on models of computation, complexity theory, data structures, and efficient computation in many recognized sub-disciplines of Theoretical Computer Science.

The SAGE Handbook of Complexity and Management is the first substantive scholarly work to provide a map of the state of art research in the growing field emerging at the intersection of complexity science and management studies. Edited and written by internationally respected scholars from management and related disciplines, the Handbook will be the definitive reference source for understanding the implications of complexity science for management research and practice. Part One: Foundations introduces complexity science and its implications for the foundations of scientific knowledge, including management knowledge. Part Two: Applications presents the numerous ways in which complexity science models and tools, as well as complexity thinking, are being applied to management and organizational phenomena and the insights gained as a result. Part Three: Interfaces highlights how complexity science is transforming various non-management fields and, in so doing, creating exciting interfaces for bridging between management and related disciplines.

It seems as if attempts to use knowledge to understand and manage social networks are everywhere. Millions, if not billions, of dollars are being spent in an attempt to derail terrorist networks, with much of it being invested in making sense of massive data streams. There is growing concern that much of this money is being squandered on approaches that will never deliver on their promises. Our armed forces are being prepared to combat terrorist threats by the introduction of “network centric approaches” and “digital battlefields” – basically attempts to provide warfighters with a complete picture of the battlespace. However, the experience of practitioners suggests that the “data smog” this creates is actually counterproductive. From the arena of politics, the recent invigorating battle between senators Clinton and Obama has thrown the spotlight on the deficiencies in political polling (Economist, 2008b). Changes in the structure of the situation (e.g. high turnouts) have thrown the whole industry into chaos. Complexity is being discounted and the results are stark. The conclusion formed in the media was that the situation was wildly unpredictable (so anyone’s to win), and ended up having real consequences for the Democratic challenger in November 2008 (Baldwin, 2008). Turning to business, we find that Société Générale recently lost $7.2bn as the result of a single rogue trader making a series of bogus transactions amid turbulent markets in 2007 and 2008. There has been much speculation on what was known, when it was known, and who knew it. In other words, we have speculation that this is an example of the role of knowledge in the mismanagement of social networks – with spectacular effect. At a glance, the problems highlighted above seem positively overwhelming. Where do you start? But start we must. Simple “cause and effect” thinking doesn’t seem to be able to cut the mustard. There is broad agreement that even if the Kyoto targets were fully met, on schedule, by 2100 it would only delay the warming of the planet by six years (Parry et al., 1998). We need to utilize knowledge in new ways…or maybe uncover insights from old ways. It is hard to think of something more worthy of attention that the role of knowledge in the management of complex systems. In Volume 4 of the Managing the Complex Series we have brought together seventeen essays from authors around the globe to explore the complex systems view of knowledge and its role in social networks. Contributors explore such topics as: the limitations to our knowledge of complex systems, the transfer of knowledge from local to global levels, collaborative knowledge generation, decision making in complex multi-stakeholder situations, organizational learning and innovation, all through the lens of the emerging field of complexity science. The editors hope that this volume will give theorists further avenues to explore in their attempts to understand knowledge creation, maintenance and distribution, and also provide practitioners with new tools to apply in the complex and messy real world.

This book gives a wide-ranging description of the many facets of complex dynamic networks and systems within an infrastructure provided by integrated control and supervision: envisioning, design, experimental exploration, and implementation. The theoretical contributions and the case studies presented can reach control goals beyond those of stabilization and output regulation or even of adaptive control. Reporting on work of the Control of Complex Systems (COSY) research program, Complex Systems follows from and expands upon an earlier collection: Control of Complex Systems by introducing novel theoretical techniques for hard-to-control networks and systems. The major common feature of all the superficially diverse contributions encompassed by this book is that of spotting and exploiting possible areas of mutual reinforcement between control, computing and communications. These help readers to achieve not only robust stable plant system operation but also properties such as collective adaptivity, integrity and survivability at the same time retaining desired performance quality. Applications in the individual chapters are drawn from: • the general implementation of model-based diagnosis and systems engineering in medical technology, in communication, and in power and airport networks; • the creation of biologically inspired control brains and safety-critical human–machine systems, • process-industrial uses; • biped robots; • large space structures and unmanned aerial vehicles; and • precision servomechanisms and other advanced technologies. Complex Systems provides researchers from engineering, applied mathematics and computer science backgrounds with innovative theoretical and practical insights into the state-of-the-art of complex networks and systems research. It employs physical implementations and extensive computer simulations. Graduate students specializing in complex-systems research will also learn much from this collection./pp

A comprehensive text that reviews the methods and technologies that explore emergent behavior in complex systems engineering in multidisciplinary fields In Emergent Behavior in Complex Systems Engineering, the authors present the theoretical considerations and the tools required to enable the study of emergent behaviors in manmade systems. Information Technology is key to today’s modern world. Scientific theories introduced in the last five decades can now be realized with the latest computational infrastructure. Modeling and simulation, along with Big Data technologies are at the forefront of such exploration and investigation. The text offers a number of simulation-based methods, technologies, and approaches that are designed to encourage the reader to incorporate simulation technologies to further their understanding of emergent behavior in complex systems. The authors present a resource for those designing, developing, managing, operating, and maintaining systems, including system of systems. The guide is designed to help better detect, analyse, understand, and manage the emergent behaviour inherent in complex systems engineering in order to reap the benefits of innovations and avoid the dangers of unforeseen consequences. This vital resource: Presents coverage of a wide range of simulation technologies Explores the subject of emergence through the lens of Modeling and Simulation (M&S) Offers contributions from authors at the forefront of various related disciplines such as philosophy, science, engineering, sociology, and economics Contains information on the next generation of complex systems engineering Written for researchers, lecturers, and students, Emergent Behavior in Complex Systems Engineering provides an overview of the current discussions on complexity and emergence, and shows how systems engineering methods in general and simulation methods in particular can help in gaining new insights in complex systems engineering.

The interaction paradigm is a new conceptualization of computational phenomena that emphasizes interaction over algorithms, reflecting the shift in technology from main-frame number-crunching to distributed intelligent networks with graphical user interfaces. The book is arranged in four sections: "Introduction", comprising three chapters that explore and summarize the fundamentals of interactive computation; "Theory" with six chapters, each discussing a specific aspect of interaction; "Applications," five chapters showing how this principle is applied in subdisciplines of computer science; and "New Directions," presenting four multidisciplinary applications. The book challenges traditional Turing machine-based answers to fundamental questions of problem solving and the scope of computation.