Complexity Science

"Put together one of the world's best science writers with one of the universe's most fascinating subjects and you are bound to produce a wonderful book. . . . The subject of complexity is vital and

Contains papers from two 1998 conferences on the relationships between managing organizations and the science of complex systems. Early chapters explain how complexity science relates to modern manage

Based on more than three decades of observation, Robert Jervis concludes in this provocative book that the very foundations of many social science theories--especially those in political science--are

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. Complexit

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 understand

The editors have extracted and summarized the core of real scientific progress in postmodern science in order to form a list of conceptual tools it has provided or refined, and to point out their sign

Combining insights from the new science of complexity with insights from psychoanalysis, Stacey posits that repressing the anxiety caused by the unstable, ever-changing nature of today's business worl

These notes are based on a series of lectures given at the Advanced Research Institute of Discrete Applied Mathematics held at Rutgers University. Their aim is to link together algorithmic problems arising in knot theory, statistical physics and classical combinatorics. Apart from the theory of computational complexity concerned with enumeration problems, introductions are given to several of the topics treated, such as combinatorial knot theory, randomised approximation algorithms, percolation and random cluster models. To researchers in discrete mathematics, computer science and statistical physics, this book will be of great interest, but any non-expert should find it an appealing guide to a very active area of research.

This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix no

Two pioneering anthropologists reveal how complexity science can help us better understand how societies change over timeOver the past two decades, anthropologist J. Stephen Lansing and geneticist Mur

Two pioneering anthropologists reveal how complexity science can help us better understand how societies change over timeOver the past two decades, anthropologist J. Stephen Lansing and geneticist Mur

Intractability is a growing concern across the cognitive sciences: while many models of cognition can describe and predict human behavior in the lab, it remains unclear how these models can scale to situations of real-world complexity. Cognition and Intractability is the first book to provide an accessible introduction to computational complexity analysis and its application to questions of intractability in cognitive science. Covering both classical and parameterized complexity analysis, it introduces the mathematical concepts and proof techniques that can be used to test one's intuition of (in)tractability. It also describes how these tools can be applied to cognitive modeling to deal with intractability, and its ramifications, in a systematic way. Aimed at students and researchers in philosophy, cognitive neuroscience, psychology, artificial intelligence, and linguistics who want to build a firm understanding of intractability and its implications in their modeling work, it is an id

Intractability is a growing concern across the cognitive sciences: while many models of cognition can describe and predict human behavior in the lab, it remains unclear how these models can scale to situations of real-world complexity. Cognition and Intractability is the first book to provide an accessible introduction to computational complexity analysis and its application to questions of intractability in cognitive science. Covering both classical and parameterized complexity analysis, it introduces the mathematical concepts and proof techniques that can be used to test one's intuition of (in)tractability. It also describes how these tools can be applied to cognitive modeling to deal with intractability, and its ramifications, in a systematic way. Aimed at students and researchers in philosophy, cognitive neuroscience, psychology, artificial intelligence, and linguistics who want to build a firm understanding of intractability and its implications in their modeling work, it is an id

Despite its worldwide following, high levels of investment and scientific complexity, there is a lack of evidence-based literature on the science of human performance in motorsport. Focusing on the ph

Golf is perhaps the most complicated simple game ever invented. Watching the professionals gives you only a glimpse of the complexity of what is happening, with each shot involving biomechanics, aerod

Mice are used as model organisms across a wide range of fields in science today—but it is far from obvious how studying a mouse in a maze can help us understand human problems like alcoholism or

Mice are used as model organisms across a wide range of fields in science today—but it is far from obvious how studying a mouse in a maze can help us understand human problems like alcoholism or

The Complexity of Self Government represents a revolutionary approach to political science. Bottom-up theory turns political and social analysis upside down by focusing analytic attention not on vacuous abstractions but on the individual men and women who either consciously or inadvertently create the institutions within which they live. Understanding this practical level of human activity is made possible through complexity theory, recently developed in computer models, but of wider use in understanding everyday human behaviour. To this complexity framework, the book adds social science to give life and colour to the analytical picture: micro-sociology from Garfinkel and Goffman, anthropology from Bourdieu, and non-technical game theory based on Thomas Schelling's microanalytics, to give rigour and bite. Theoretical examples include India's Mumbai, Iran, the marshes of southern Iraq, Berlusconi's Italy, backcountry China, Zimbabwe, and Nelson Mandela's revolution in South Africa.

The Complexity of Self Government represents a revolutionary approach to political science. Bottom-up theory turns political and social analysis upside down by focusing analytic attention not on vacuous abstractions but on the individual men and women who either consciously or inadvertently create the institutions within which they live. Understanding this practical level of human activity is made possible through complexity theory, recently developed in computer models, but of wider use in understanding everyday human behaviour. To this complexity framework, the book adds social science to give life and colour to the analytical picture: micro-sociology from Garfinkel and Goffman, anthropology from Bourdieu, and non-technical game theory based on Thomas Schelling's microanalytics, to give rigour and bite. Theoretical examples include India's Mumbai, Iran, the marshes of southern Iraq, Berlusconi's Italy, backcountry China, Zimbabwe, and Nelson Mandela's revolution in South Africa.

The concept of “chaos”, and chaos theory, though it is a field of study specifically in the field of mathematics with applications in physics, engineering, economics, management, and education, has al

This book studies social phenomena in a new way, by making judicious use of computer technology. The book addresses the entire spectrum of classic studies in social science, from experiments to the co

Complexity science--made possible by modern analytical and computational advances--is changing the way we think about social systems and social theory. Unfortunately, economists' policy models have no

Complexity science--made possible by modern analytical and computational advances--is changing the way we think about social systems and social theory. Unfortunately, economists' policy models have no

The field of human sexuality is one of ever-increasing complexity, particularly for Christian therapists and psychologists seeking to be faithful to Scripture, informed by science and sensitive to cul

"Science as Psychology reveals the complexity and richness of rationality by demonstrating how social relationships, emotion, culture, and identity are implicated in the problem-solving practices of l

Uncorked quenches our curiosity about the inner workings of one of the world's most prized beverages. Esteemed for its freshness, vitality, and sensuality, champagne is a wine of great complexity. Mys

"Extreme Events and Natural Hazards: The Complexity Perspective" examines recent developments in complexity science that provide a new approach to understanding extreme events. This understanding is c

This advanced textbook on modeling, data analysis and numerical techniques for marine science has been developed from a course taught by the authors for many years at the Woods Hole Oceanographic Institute. The first part covers statistics: singular value decomposition, error propagation, least squares regression, principal component analysis, time series analysis and objective interpolation. The second part deals with modeling techniques: finite differences, stability analysis and optimization. The third part describes case studies of actual ocean models of ever increasing dimensionality and complexity, starting with zero-dimensional models and finishing with three-dimensional general circulation models. Throughout the book hands-on computational examples are introduced using the MATLAB programming language and the principles of scientific visualization are emphasised. Ideal as a textbook for advanced students of oceanography on courses in data analysis and numerical modeling, the boo

In a global market economy, a viable business cannot be locked into a single form or function anymore. Rather, success is contingent upon a self-renewing capacity to spontaneously create structures, f

Presenting a comprehensive discussion of general circulation models of the atmosphere, this book covers their historical and contemporary development, their societal context, and current efforts to integrate these models into wider Earth-system models. Leading researchers provide unique perspectives on the scientific breakthroughs, overarching themes, critical applications, and future prospects for atmospheric general circulation models. Key interdisciplinary links to other subject areas such as chemistry, oceanography and ecology are also highlighted. This book is a core reference for academic researchers and professionals involved in atmospheric physics, meteorology and climate science, and can be used as a resource for graduate-level courses in climate modeling and numerical weather prediction. Given the critical role that atmospheric general circulation models are playing in the intense public discourse on climate change, it is also a valuable resource for policy makers and all tho

This collection of sixteen articles on Service Oriented Architecture (SOA) presents current scholarship in data and service interoperability and discovery in business complex, distributed computer arc

Science as Psychology reveals the complexity and richness of rationality by demonstrating how social relationships, emotion, culture, and identity are implicated in the problem-solving practices of laboratory scientists. In this study, the authors gather and analyze interview and observational data from innovation-focused laboratories in the engineering sciences to show how the complex practices of laboratory research scientists provide rich psychological insights, and how a better understanding of science practice facilitates understanding of human beings more generally. The study focuses not on dismantling the rational core of scientific practice, but on illustrating how social, personal, and cognitive processes are intricately woven together in scientific thinking. The book is thus a contribution to science studies, the psychology of science, and general psychology.

Increasing size and complexity of software and hardware systems makes it harder to ensure their reliability. At the same time, the issues of autonomous computing become more critical as we more and mo

The focus of this book is the P versus NP Question and the theory of NP-completeness. It also provides adequate preliminaries regarding computational problems and computational models. The P versus NP Question asks whether or not finding solutions is harder than checking the correctness of solutions. An alternative formulation asks whether or not discovering proofs is harder than verifying their correctness. It is widely believed that the answer to these equivalent formulations is positive, and this is captured by saying that P is different from NP. Although the P versus NP Question remains unresolved, the theory of NP-completeness offers evidence for the intractability of specific problems in NP by showing that they are universal for the entire class. Amazingly enough, NP-complete problems exist, and furthermore hundreds of natural computational problems arising in many different areas of mathematics and science are NP-complete.

The focus of this book is the P versus NP Question and the theory of NP-completeness. It also provides adequate preliminaries regarding computational problems and computational models. The P versus NP Question asks whether or not finding solutions is harder than checking the correctness of solutions. An alternative formulation asks whether or not discovering proofs is harder than verifying their correctness. It is widely believed that the answer to these equivalent formulations is positive, and this is captured by saying that P is different from NP. Although the P versus NP Question remains unresolved, the theory of NP-completeness offers evidence for the intractability of specific problems in NP by showing that they are universal for the entire class. Amazingly enough, NP-complete problems exist, and furthermore hundreds of natural computational problems arising in many different areas of mathematics and science are NP-complete.

The increased complexity of embedded systems coupled with quick design cycles to accommodate faster time-to-market requires increased system design productivity that involves both model-based design a

While many books have discussed methodological advances in nonlinear dynamical systems theory (NDS), this volume is unique in its focus on NDS's role in the development of psychological theory. After an introductory chapter covering the fundamentals of chaos, complexity and other nonlinear dynamics, subsequent chapters provide in-depth coverage of each of the specific topic areas in psychology. A concluding chapter takes stock of the field as a whole, evaluating important challenges for the immediate future. The chapters are written by experts in the use of NDS in each of their respective areas, including biological, cognitive, developmental, social, organizational and clinical psychology. Each chapter provides an in-depth examination of theoretical foundations and specific applications and a review of relevant methods. This edited collection represents the state of the art in NDS science across the disciplines of psychology.

The insights of complexity science can allow today’s managers to embrace the challenges and uncertainty of the twenty-first century, and successfully oversee organizational change and developmen