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Robert Wright challenges the conventional view that biological evolution and human history are aimless. Employing game theory - the logic of "zero-sum" and "non-zero-sum" games - he isolates the impetus behind life's basic direction: the impetus that, via biological evolution, created complex, intelligent animals, and then via cultural evolution, pushed the human species towards deeper and vaster social complexity. In this view, the coming of today's independent global society was "on the cards" - not quite inevitable, but, as Wright puts it, "so probable as to inspire wonder". Wright takes on some of the past century's most prominent thinkers, including Isaiah Berlin, Karl Popper, Stephen Jay Gould, and Richard Dawkins, arguing that a coolly specific appraisal of humanity's three-billion-year past can give new spiritual meaning to the present and even offer political guidance for the future.

At the beginning of Nonzero, Robert Wright sets out to "define the arrow of the history of life, from the primordial soup to the World Wide Web." Twenty-two chapters later, after a sweeping and vivid narrative of the human past, he has succeeded — and has mounted a powerful challenge to the conventional view that evolution and human history are aimless.Ingeniously employing game theory — the logic of "zero-sum" and "non-zero-sum" games — Wright isolates the impetus behind life's basic direction: the impetus that, via biological evolution, created complex, intelligent animals and then, via cultural evolution, pushed the human species toward deeper and vaster social complexity. In this view, the coming of today's interdependent global society was "in the cards" — not quite inevitable, perhaps, but, as Wright puts it, "so probable as to inspire wonder." So probable, indeed, as to invite speculation about higher purpose, especially in light of "the phase of history that seems to lie immediately ahead: a social, political, and even moral culmination of sorts."In a work of vast erudition and pungent wit, Wright takes on some of the past century's most prominent thinkers, including Isaiah Berlin, Karl Popper, Stephen Jay Gould, and Richard Dawkins. He finds evidence for his position in unexpected corners, from native American hunter-gatherer societies and Polynesian chiefdoms to medieval Islamic commerce and precocious Chinese technology; from conflicts of interest among a cell's genes to discord at the World Trade Organization.Wright argues that a coolly scientific appraisal of humanity's three-billion-year past can give new spiritual meaning to the present and even offer political guidance for the future. Nonzero will change the way people think about the human prospect.

This book presents the theory of dynamical systems with nonzero Lyapunov exponents, offering a rigorous mathematical foundation for deterministic chaos - the appearance of "chaotic" motions in pure deterministic dynamical systems. These ideas and methods are used in many areas of mathematics as well as in physics, biology, and engineering. Despite the substantial amount of research on the subject, there have been relatively few attempts to summarize and unify results in a single manuscript. This comprehensive book can be used as a reference or as a supplement to an advanced course on dynamical systems.

This book presents the theory of dynamical systems with nonzero Lyapunov exponents, offering a rigorous mathematical foundation for deterministic chaos - the appearance of "chaotic" motions in pure deterministic dynamical systems. These ideas and methods are used in many areas of mathematics as well as in physics, biology, and engineering. Despite the substantial amount of research on the subject, there have been relatively few attempts to summarize and unify results in a single manuscript. This comprehensive book can be used as a reference or as a supplement to an advanced course on dynamical systems.

Discover New Methods for Dealing with High-Dimensional Data A sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data. Top experts in this rapidly evolving field, the authors describe the lasso for linear regression and a simple coordinate descent algorithm for its computation. They discuss the application of ℓ1 penalties to generalized linear models and support vector machines, cover generalized penalties such as the elastic net and group lasso, and review numerical methods for optimization. They also present statistical inference methods for fitted (lasso) models, including the bootstrap, Bayesian methods, and recently developed approaches. In addition, the book examines matrix decomposition, sparse multivariate analysis, graphical models, and compressed sensing. It concludes with a survey of theoretical results for the lasso. In this age of big data, the number of features measured on a person or object can be large and might be larger than the number of observations. This book shows how the sparsity assumption allows us to tackle these problems and extract useful and reproducible patterns from big datasets. Data analysts, computer scientists, and theorists will appreciate this thorough and up-to-date treatment of sparse statistical modeling.

In The Evolution of God, Robert Wright, award-winning author of the bestselling books Nonzero and The Moral Animal, takes us on a sweeping journey through religious history, from the Stone Age to the Information Age, unveiling along the way an astonishing discovery: that there is a hidden pattern in the way that Judaism, Christianity and Islam have all evolved.Through the prisms of archaeology, theology, evolutionary psychology and a careful re-reading of the scriptures, Wright's findings repeatedly overturn conventional wisdom and basic assumptions about the great monotheistic faiths.Looking at the forces that have moved the Abrahamic faiths away from belligerence and intolerance to a higher moral plane, Wright finds that this previously unrecognized evolutionary logic points not toward continued religious extremism as the media would have us believe, but towards future harmony.

Discover New Methods for Dealing with High-Dimensional Data A sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data. Top experts in this rapidly evolving field, the authors describe the lasso for linear regression and a simple coordinate descent algorithm for its computation. They discuss the application of ℓ1 penalties to generalized linear models and support vector machines, cover generalized penalties such as the elastic net and group lasso, and review numerical methods for optimization. They also present statistical inference methods for fitted (lasso) models, including the bootstrap, Bayesian methods, and recently developed approaches. In addition, the book examines matrix decomposition, sparse multivariate analysis, graphical models, and compressed sensing. It concludes with a survey of theoretical results for the lasso. In this age of big data, the number of features measured on a person or object can be large and might be larger than the number of observations. This book shows how the sparsity assumption allows us to tackle these problems and extract useful and reproducible patterns from big datasets. Data analysts, computer scientists, and theorists will appreciate this thorough and up-to-date treatment of sparse statistical modeling.