For centuries, scientific thought was focused on bringing order to the natural world. But even as relativity and quantum mechanics undermined that rigid certainty in the first half of the twentieth century, the scientific community clung to the idea that any system, no matter how complex, could be reduced to a simple pattern. In the 1960s, a small group of radical thinkers began to take that notion apart, placing new importance on the tiny experimental irregularities that scientists had long learned to ignore. Miniscule differences in data, they said, would eventually produce massive ones—and complex systems like the weather, economics, and human behavior suddenly became clearer and more beautiful than they had ever been before.In this seminal work of scientific writing, James Gleick lays out a cutting edge field of science with enough grace and precision that any reader will be able to grasp the science behind the beautiful complexity of the world around us. With more than a million copies sold, Chaos is “a groundbreaking book about what seems to be the future of physics” by a writer who has been a finalist for both the Pulitzer Prize and the National Book Award, the author of Time Travel: A History and Genius: The Life and Science of Richard Feynman (Publishers Weekly).
By showing us the true nature of chance and revealing the psychological illusions that cause us to misjudge the world around us, Mlodinow gives us the tools we need to make more informed decisions. From the classroom to the courtroom and from financial markets to supermarkets, Mlodinow's intriguing and illuminating look at how randomness, chance, and probability affect our daily lives will intrigue, awe, and inspire.
From the Trade Paperback edition.
Scientists have recently discovered a new law of nature and its footprints are virtually everywhere-- in the spread of forest fires, mass extinctions, traffic jams, earthquakes, stock-market fluctuations, the rise and fall of nations, and even trends in fashion, music and art. Wherever we look, the world is modelled on a simple template: like a steep pile of sand, it is poised on the brink of instability, with avalanches-- in events, ideas or whatever-- following a universal pattern of change. This remarkable discovery heralds what Mark Buchanan calls the new science of 'ubiquity', a science whose secret lies in the stuff of the everyday world. Combining literary flair with scientific rigour, this enthralling book documents the coming revolution by telling the story of the researchers' exploration of the law, their ingenious work and unexpected insights.
Buchanan reveals that we are witnessing the emergence of an extraordinarily powerful new field of science that will help us comprehend the bewildering and unruly rhythms that dominate our lives and may even lead to a true science of the dynamics of human culture and history.
The Second Edition is completely revised and provides additional review material on linear algebra as well as complete coverage of elementary linear programming. Other topics covered include: the Duality Theorem; transportation problems; the assignment problem; and the maximal flow problem. New figures and exercises are provided and the authors have updated all computer applications.More review material on linear algebraElementary linear programming covered more efficientlyPresentation improved, especially for the duality theorem, transportation problems, the assignment problem, and the maximal flow problemNew figures and exercisesComputer applications updatedNew guide to inexpensive linear programming software for personal computers
John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.
Imagine trying to understand a stained glass window by breaking it into pieces and examining it one shard at a time. While you could probably learn a lot about each piece, you would have no idea about what the entire picture looks like. This is reductionism--the idea that to understand the world we only need to study its pieces--and it is how most social scientists approach their work.
In A Crude Look at the Whole, social scientist and economist John H. Miller shows why we need to start looking at whole pictures. For one thing, whether we are talking about stock markets, computer networks, or biological organisms, individual parts only make sense when we remember that they are part of larger wholes. And perhaps more importantly, those wholes can take on behaviors that are strikingly different from that of their pieces.
Miller, a leading expert in the computational study of complex adaptive systems, reveals astounding global patterns linking the organization of otherwise radically different structures: It might seem crude, but a beehive's temperature control system can help predict market fluctuations and a mammal's heartbeat can help us understand the "heartbeat" of a city and adapt urban planning accordingly. From enduring racial segregation to sudden stock market disasters, once we start drawing links between complex systems, we can start solving what otherwise might be totally intractable problems.
Thanks to this revolutionary perspective, we can finally transcend the limits of reductionism and discover crucial new ideas. Scientifically founded and beautifully written, A Crude Look at the Whole is a powerful exploration of the challenges that we face as a society. As it reveals, taking the crude look might be the only way to truly see.
Boizumault introduces the specific problems posed by the implementation of Prolog, studies and compares different solutions--notably those of the schools of Marseilles and Edinburgh--and concludes with three examples of implementation. Major points of interest include identifying the important differences in implementing unification and resolution; presenting three features of Prolog II--infinite trees, dif, and freeze--that introduce constraints; thoroughly describing Warren's Abstract Machine (WAM); and detailing a Lisp imple-mentation of Prolog.
Originally published in 1993.
The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
An introductory chapter offers a systematic and organized approach to problem formulation. Subsequent chapters explore geometric motivation, proof techniques, linear algebra and algebraic steps related to the simplex algorithm, standard phase 1 problems, and computational implementation of the simplex algorithm. Additional topics include duality theory, issues of sensitivity and parametric analysis, techniques for handling bound constraints, and network flow problems. Helpful appendixes conclude the text, including a new addition that explains how to use Excel to solve linear programming problems.
The scope of the book is broad: it not only describes KAM theory in some detail, but also presents its historical context (thus showing why it was a “breakthrough”). Also discussed are applications of KAM theory (especially to celestial mechanics and statistical mechanics) and the parts of mathematics and physics in which KAM theory resides (dynamical systems, classical mechanics, and Hamiltonian perturbation theory).
Although a number of sources on KAM theory are now available for experts, this book attempts to fill a long-standing gap at a more descriptive level. It stands out very clearly from existing publications on KAM theory because it leads the reader through an accessible account of the theory and places it in its proper context in mathematics, physics, and the history of science.
Safety-II changes safety management from protective safety and a focus on how things can go wrong, to productive safety and a focus on how things can and do go well. For Safety-II, the aim is not just the elimination of hazards and the prevention of failures and malfunctions but also how best to develop an organisation’s potentials for resilient performance – the way it responds, monitors, learns, and anticipates. That requires models and methods that go beyond the Safety-I toolbox. This book introduces a comprehensive approach for the management of Safety-II, called the Resilience Assessment Grid (RAG). It explains the principles of the RAG and how it can be used to develop the resilience potentials. The RAG provides four sets of diagnostic and formative questions that can be tailored to any organisation. The questions are based on the principles of resilience engineering and backed by practical experience from several domains.
Safety-II in Practiceis for both the safety professional and academic reader. For the professional, it presents a workable method (RAG) for the management of Safety-II, with a proven track record. For academic and student readers, the book is a concise and practical presentation of resilience engineering.