This book takes the reader beyond net effects and main and interaction effects thinking and methods. Complexity theory includes the tenet that recipes are more important than ingredients—any one antecedent (X) condition is insufficient for a consistent outcome (Y) (e.g., success or failure) even though the presence of certain antecedents may be necessary. A second tenet: modeling contrarian cases is useful because a high or low score for any given antecedent condition (X) associates with a high Y, low Y, and is irrelevant for high/low Y in some recipes in the same data set. Third tenet: equifinality happens—several recipes indicate high/low outcomes.
Chaos and complexity are the new buzz words in both science and contemporary society. The ideas they represent have enormous implications for the way we understand and engage with the world. Complexity Theory and the Social Sciences introduces students to the central ideas which surround the chaos/complexity theories. It discusses key concepts before using them as a way of investigating the nature of social research. By applying them to such familiar topics as urban studies, education and health, David Byrne allows readers new to the subject to appreciate the contribution which complexity theory can make to social research and to illuminating the crucial social issues of our day.
The underlying idea and motive for the book is that the notion of complexity may humanize the social sciences, may conceive the complex human being as more human, and turn reality as assumed in our doing social science into a more complex, that is a richer reality for all. The main focus of this book is on new thinking in complexity, with complexity to be taken as derived from the Latin word complexus: ‘that which is interwoven.’ The trans-disciplinary approach advocated here will be trans-disciplinary in two ways: firstly, by going beyond the separate disciplines within the fields of both natural sciences and social sciences, and, secondly, by going beyond the separate cultures of the natural sciences and of the social sciences and humanities.
New and classical results in computational complexity, including interactive proofs, PCP, derandomization, and quantum computation. Ideal for graduate students.
“If you liked Chaos, you’ll love Complexity. Waldrop creates the most exciting intellectual adventure story of the year” (The Washington Post). In a rarified world of scientific research, a revolution has been brewing. Its activists are not anarchists, but rather Nobel Laureates in physics and economics and pony-tailed graduates, mathematicians, and computer scientists from all over the world. They have formed an iconoclastic think-tank and their radical idea is to create a new science: complexity. They want to know how a primordial soup of simple molecules managed to turn itself into the first living cell—and what the origin of life some four billion years ago can tell us about the process of technological innovation today. This book is their story—the story of how they have tried to forge what they like to call the science of the twenty-first century. “Lucidly shows physicists, biologists, computer scientists and economists swapping metaphors and reveling in the sense that epochal discoveries are just around the corner . . . [Waldrop] has a special talent for relaying the exhilaration of moments of intellectual insight.” —The New York Times Book Review “Where I enjoyed the book was when it dove into the actual question of complexity, talking about complex systems in economics, biology, genetics, computer modeling, and so on. Snippets of rare beauty here and there almost took your breath away.” —Medium “[Waldrop] provides a good grounding of what may indeed be the first flowering of a new science.” —Publishers Weekly
In Complexity and Postmodernism, Paul Cilliers explores the idea of complexity in the light of contemporary perspectives from philosophy and science. Cilliers offers us a unique approach to understanding complexity and computational theory by integrating postmodern theory (like that of Derrida and Lyotard) into his discussion. Complexity and Postmodernism is an exciting and an original book that should be read by anyone interested in gaining a fresh understanding of complexity, postmodernism and connectionism.
Offering a critique of the humanist paradigm in contemporary social theory, Qualitative Complexity is the first comprehensive sociological analysis of complexity theory. Drawing from sources in sociology, philosophy, complexity theory, 'fuzzy logic', systems theory, cognitive science and evolutionary biology, John Smith and Chris Jenks present a new series of interdisciplinary perspectives on the sociology of complex, self-organizing structures.
Since its initial publication, this highly respected text has provided students with a critical review of the major research paradigms in the social sciences and the logics or strategies of enquiry associated with them. This second edition has been revised and updated.
Complexity theory illuminates the many interactions between natural and social systems, providing a better understanding of the general principles that can help solve some of today's most pressing environmental issues. Complexity theory was developed from key ideas in economics, physics, biology, and the social sciences and contributes to important new concepts for approaching issues of environmental sustainability such as resilience, scaling, and networks. Complexity Theory for a Sustainable Future is a hands-on treatment of this exciting new body of work and its applications, bridging the gap between theoretical and applied perspectives in the management of complex adaptive systems. Focusing primarily on natural resource management and community-based conservation, the book features contributions by leading scholars in the field, many of whom are among the leaders of the Resilience Alliance. Theoreticians will find a valuable synthesis of new ideas on resilience, sustainability, asymmetries, information processing, scaling, and networks. Managers and policymakers will benefit from the application of these ideas to practical approaches and empirical studies linked to social-ecological systems. Chapters present new twists on such existing approaches as scenario planning, scaling analyses, and adaptive management, and the book concludes with recommendations on how to manage natural resources, how to involve stakeholders in the dynamics of a system, and how to explain the difficult topic of scale. A vital reference for an emerging discipline, this volume provides a clearer understanding of the conditions required for systems self-organization, since the capacity of any system to self-organize is crucial for its sustainability over time.
