The boundaries between simple and complicated, and complicated and complex system designations are fuzzy and debatable, even using quantitative measures of complexity. However, if you are a biomedical engineer, a biologist, physiologist, economist, politician, stock market speculator, or politician, you have encountered complex systems. Furthermore, your success depends on your ability to successfully interact with and manage a variety of complex systems. In order not to be blindsided by unexpected results, we need a systematic, comprehensive way of analyzing, modeling, and simulating complex systems to predict non-anticipated outcomes. In its engaging first chapters, the book introduces complex systems, Campbell's Law, and the Law of Unintended Consequences, and mathematics necessary for conversations in complex systems. Subsequent chapters illustrate concepts via commonly studied biological mechanisms. The final chapters focus on higher-level complexity problems, and introduce complexity in economic systems. Designed as a reference for biologists and biological engineers, Introduction to Complexity and Complex Systems lends itself to use in a classroom course to introduce advanced students studying biomedical engineering, biophysics, or physiology to complex systems. Engaging and illustrative, this book aids scientists and decision makers in managing biological complexity and complex systems.

Social Complexity and Complex Systems in Archaeology turns to complex systems thinking in search of a suitable framework to explore social complexity in Archaeology. Social complexity in archaeology is commonly related to properties of complex societies such as states, as opposed to so-called simple societies such as tribes or chiefdoms. These conceptualisations of complexity are ultimately rooted in Eurocentric perspectives with problematic implications for the field of archaeology. This book provides an in-depth conceptualisation of social complexity as the core concept in archaeological and interdisciplinary studies of the past, integrating approaches from complex systems thinking, archaeological theory, social practice theory, and sustainability and resilience science. The book covers a long-term perspective of social change and stability, tracing the full cycle of complexity trajectories, from emergence and development to collapse, regeneration and transformation of communities and societies. It offers a broad vision on social complexity as a core concept for the present and future development of archaeology. This book is intended to be a valuable resource for students and scholars in the field of archaeology and related disciplines such as history, anthropology, sociology, as well as the natural sciences studying human-environment interactions in the past.

With industrial systems becoming ever more mechanized and reliant on advanced technology, the complexity of equipment, especially in risky industries, is increasing on a daily basis. A thorough understanding of operations and providing safety for these complex systems has become a firm requirement for many. This book offers the knowledge required by safety professionals to provide and maintain the safety of engineering complex systems. Through a scientific and engineering approach to designing, implementing, operating, and maintaining complex systems, Learning and Relearning Equipment Complexity: Achieving Safety in Engineering Complex Systems details the need for more engineering and scientific knowledge to understand and maintain their safety. It gives clear explanations of reasons for a system’s complexity, based on control systems and non-linear dynamics. In addition, the book addresses the necessary changes in the approach and the procedures for the safety assessment of engineering complex systems. The reader will develop a thorough understanding of what complex systems are, why they are complex, and how they are utilized. This book will appeal to any safety professional tasked with complex systems. This extends to professionals in risky industries such as aviation, nuclear power, chemicals, railway and transport, and pharmaceuticals.

Multi-Chaos, Fractal and Multi-Fractional Artificial Intelligence of Different Complex Systems addresses different uncertain processes inherent in the complex systems, attempting to provide global and robust optimized solutions distinctively through multifarious methods, technical analyses, modeling, optimization processes, numerical simulations, case studies as well as applications including theoretical aspects of complexity. Foregrounding Multi-chaos, Fractal and Multi-fractional in the era of Artificial Intelligence (AI), the edited book deals with multi- chaos, fractal, multifractional, fractional calculus, fractional operators, quantum, wavelet, entropy-based applications, artificial intelligence, mathematics-informed and data driven processes aside from the means of modelling, and simulations for the solution of multifaceted problems characterized by nonlinearity, non-regularity and self-similarity, frequently encountered in different complex systems. The fundamental interacting components underlying complexity, complexity thinking, processes and theory along with computational processes and technologies, with machine learning as the core component of AI demonstrate the enabling of complex data to augment some critical human skills. Appealing to an interdisciplinary network of scientists and researchers to disseminate the theory and application in medicine, neurology, mathematics, physics, biology, chemistry, information theory, engineering, computer science, social sciences and other far-reaching domains, the overarching aim is to empower out-of-the-box thinking through multifarious methods, directed towards paradoxical situations, uncertain processes, chaotic, transient and nonlinear dynamics of complex systems. Constructs and presents a multifarious approach for critical decision-making processes embodying paradoxes and uncertainty. Includes a combination of theory and applications with regard to multi-chaos, fractal and multi-fractional as well as AI of different complex systems and many-body systems. Provides readers with a bridge between application of advanced computational mathematical methods and AI based on comprehensive analyses and broad theories.

Complexity and Complex Thermoeconomic Systems describes the properties of complexity and complex thermo-economic systems as the consequence of formulations, definitions, tools, solutions and results consistent with the best performance of a system. Applying to complex systems contemporary advanced techniques, such as static optimization, optimal control, and neural networks, this book treats the systems theory as a science of general laws for functional integrities. It also provides a platform for the discussion of various definitions of complexity, complex hierarchical structures, self-organization examples, special references, and historical issues. This book is a valuable reference for scientists, engineers and graduated students in chemical, mechanical, and environmental engineering, as well as those in physics, ecology and biology, helping them better understand the complex thermodynamic systems and enhance their technical skills in research. Provides a lucid presentation of the dynamical properties of thermoeconomic systems Includes original graphical material that illustrates the properties of complex systems Written by a first-class expert in the field of advanced methods in thermodynamics

In recent years, scientists have applied the principles of complex systems science to increasingly diverse fields. The results have been nothing short of remarkable: their novel approaches have provided answers to long-standing questions in biology, ecology, physics, engineering, computer science, economics, psychology and sociology. "Unifying Themes in Complex Systems" is a well established series of carefully edited conference proceedings that serve the purpose of documenting and archiving the progress of cross-fertilization in this field. About NECSI: For over 10 years, The New England Complex Systems Institute (NECSI) has been instrumental in the development of complex systems science and its applications. NECSI conducts research, education, knowledge dissemination, and community development around the world for the promotion of the study of complex systems and its application for the betterment of society. NECSI hosts the International Conference on Complex Systems and publishes the NECSI Book Series in conjunction with Springer Publishers.

Emergence and complexity refer to the appearance of higher-level properties and behaviours of a system that obviously comes from the collective dynamics of that system's components. These properties are not directly deducible from the lower-level motion of that system. Emergent properties are properties of the "whole'' that are not possessed by any of the individual parts making up that whole. Such phenomena exist in various domains and can be described, using complexity concepts and thematic knowledges. This book highlights complexity modelling through dynamical or behavioral systems. The pluridisciplinary purposes, developed along the chapters, are able to design links between a wide-range of fundamental and applicative Sciences. Developing such links - instead of focusing on specific and narrow researches - is characteristic of the Science of Complexity that we try to promote by this contribution.

"The emphasis on change at many levels of organization is critically important as is the first attempt to integrate sophisticated theory and research in organization psychology (e.g., Gersick, Hackman) with social psychological models of development such as Moreland and Levine." --Reuben M. Baron, Emeritus, University of Connecticut "Arrow, McGrath, and Berdahl′s ′Small Groups as Complex Systems′ will change the way you think about groups, the way you think about research, and even the way you think about science." --Donelson R. Forsyth, Psychology, Virginia Commonwealth U "The book is excellent, one of those very rare works that will have substantial impact on the field. I would use the book without hesitation in any advanced graduate seminar dealing with groups." --Donelson R. Forsyth, Psychology, Virginia Commonwealth U "A conceptually elegant analysis of groups as systems. Although the systems approach has been growing more influential in various fields of social psychology in the last ten years, no one has put forward a definitive analysis that applies with fidelity the general systems approach to group processes. McGrath and his colleagues fill that gap, not by paying lip service to popular scientific concepts such as recursive causality, open systems, attractors, and complexity theory, but by fully integrating these concepts into their no-nonsense analysis of such group level processes as formation, task performance, composition, development, and termination. Empirical work is folded into the theoretical mix along the way, but the focus is unrelentingly conceptual with the result that the authors deliver on their promise of developing a powerful, unified theory of group dynamics." --Donelson R. Forsyth, Psychology, Virginia Commonwealth U "Theirs is an ambitious book. They have profound ramifications for experimental social psychology. It is worth mentioning that AMD (Arrow, McGrarth, and Berdahl) list an ethnographic approach, which often implies the adoption of hermeneutic and semiotic methods (a hallmark of the anti-Enlightenment tradition in psychology), as a possible way forward." --Yoshihisa Kashima, American Journal of Psychology What are groups? How do they behave? Arrow, McGrath, and Berdahl answer these questions by developing a general theory of small groups as complex systems. Basing their theory on concepts distilled from general systems theory, dynamical systems theory, and complexity and chaos theory, they explore groups as adaptive, dynamic systems that are driven by interactions among group members as well as between the group and its embedding contexts. In addition, they consider not only the group′s members and their distribution of attributes, but also the group′s tasks and technology in order to understand how those members, tasks, and tools are intertwined, coordinated, and adjusted. Throughout the book, the authors focus our attention on relationships among people, tools, and tasks that are activated by a combination of individual and collective purposes and goals that change and evolve as the group interacts over time.

Faced with ever-increasing complexity on a daily basis, the decision-makers of today are struggling to find the appropriate models, methods and tools to face the issues arising in complex systems across all levels of global operations. Having, in the past, resorted to outdated approaches which limit problem-solving to linear world views, we must now capitalize on complexities in order to succeed and progress in our society. This book provides a guide to harnessing the wealth inherent to complex systems. It organizes the transition to complex decision-making in all business spheres while providing many examples in various application domains. The authors offer fresh developments for understanding and mastering the global “uberization” of the economy, the post-modern management of computer-assisted production and the rise of cognitive robotics science applications.

Containing selected papers on the fundamentals and applications of Complexity Science, this multi-disciplinary book presents new approaches for resolving complex issues that cannot be resolved using conventional mathematical or software models. Complex Systems problems can occur in a variety of areas such as physical sciences and engineering, the economy, the environment, humanities and social and political sciences. Complexity Science problems, the science of open systems consisting of large numbers of diverse components engaged in rich interaction, can occur in a variety of areas such as physical sciences and engineering, the economy, the environment, humanities and social and political sciences. The global behaviour of these systems emerges from the interaction of constituent components and is unpredictable but not random. The key attribute of Complex Systems is the ability to self-organise and adapt to unpredictable changes in their environment.