For over three decades, Ray Kurzweil has been one of the most respected and provocative advocates of the role of technology in our future. In his classic The Age of Spiritual Machines , he argued that computers would soon rival the full range of human intelligence at its best. Now he examines the next step in this inexorable evolutionary process: the union of human and machine, in which the knowledge and skills embedded in our brains will be combined with the vastly greater capacity, speed, and knowledge-sharing ability of our creations.

In this new edition the author has added substantial material on Bayesian analysis, including lengthy new sections on such important topics as empirical and hierarchical Bayes analysis, Bayesian calculation, Bayesian communication, and group decision making. With these changes, the book can be used as a self-contained introduction to Bayesian analysis. In addition, much of the decision-theoretic portion of the text was updated, including new sections covering such modern topics as minimax multivariate (Stein) estimation.

Douglas Hofstadter's long-awaited return to the themes of Gödel, Escher, Bach--an original and controversial view of the nature of consciousness and identity.
Can thought arise out of matter? Can self, a soul, a consciousness, an "I" arise out of mere matter? If it cannot, then how can you or I be here?
I Am a Strange Loop argues that the key to understanding selves and consciousness is the "strange loop"--a special kind of abstract feedback loop inhabiting our brains. The most central and complex symbol in your brain or mine is the one called "I." The "I" is the nexus in our brain, one of many symbols seeming to have free will and to have gained the paradoxical ability to push particles around, rather than the reverse.
How can a mysterious abstraction be real--or is our "I" merely a convenient fiction? Does an "I" exert genuine power over the particles in our brain, or is it helplessly pushed around by the laws of physics?
These are the mysteries tackled in I Am a Strange Loop, Douglas R. Hofstadter's first book-length journey into philosophy since Gödel, Escher, Bach. Compulsively readable and endlessly thought-provoking, this is the book Hofstadter's many readers have been waiting for.

This book introduces the geometry of 3-D vision, that is, the reconstruction of 3-D models of objects from a collection of 2-D images. It details the classic theory of two view geometry and shows that a more proper tool for studying the geometry of multiple views is the so-called rank consideration of the multiple view matrix. It also develops practical reconstruction algorithms and discusses possible extensions of the theory.

图灵机是英国数学家阿兰•图灵提出的一种抽象计算模型，本书深入剖析了图灵这篇描述图灵机和可计算性的原始论文《论可计算数及其在判定性问题上的应用》。书中在详解论文的同时，也附带了大量的历史背景资料、图灵的个人经历，以及图灵机对于人们理解计算机、人类意识和宇宙所产生的影响。 本书适合所有计算机科学专业的学生、程序员或其他技术人员，同时也适合欲了解图灵生平及其构建图灵机的思维的读者阅读。

From Library Journal
This is an ambitious attempt to define and summarize ``cognitive science,'' a new field of scientific inquiry and knowledge. The author, a leading authority and researcher in this area, writes in a clear, accessible manner; yet, his book conveys the tremendous scope and complexity of this burgeoning field. He convincingly links such seemingly disparate areas as linguistics, computer science, cognitive psychology, structural anthropology, and neuroscience, and attempts to integrate both their historical development and underlying approaches to cognition. Recommended for scholars as an introductory text and for informed laypersons who want a thorough and fascinating grounding in the study of the mind and how it works.

This book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. The book is intended to support upper level undergraduate and introductory level graduate courses in machine learning.

WINNER OF THE 2005 DEGROOT PRIZE! This book is for people who want to learn probability and statistics quickly. It brings together many of the main ideas in modern statistics in one place. The book is suitable for students and researchers in statistics, computer science, data mining and machine learning. This book covers a much wider range of topics than a typical introductory text on mathematical statistics. It includes modern topics like nonparametric curve estimation, bootstrapping and classification, topics that are usually relegated to follow-up courses. The reader is assumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. The text can be used at the advanced undergraduate and graduate level.

Dramatically updating and extending the first edition, published in 1995, the second edition of The Handbook of Brain Theory and Neural Networks presents the enormous progress made in recent years in the many subfields related to the two great questions: How does the brain work? and, How can we build intelligent machines?Once again, the heart of the book is a set of almost 300 articles covering the whole spectrum of topics in brain theory and neural networks. The first two parts of the book, prepared by Michael Arbib, are designed to help readers orient themselves in this wealth of material. Part I provides general background on brain modeling and on both biological and artificial neural networks. Part II consists of "Road Maps" to help readers steer through articles in part III on specific topics of interest. The articles in part III are written so as to be accessible to readers of diverse backgrounds. They are cross-referenced and provide lists of pointers to Road Maps, background material, and related reading.The second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. It contains 287 articles, compared to the 266 in the first edition. Articles on topics from the first edition have been updated by the original authors or written anew by new authors, and there are 106 articles on new topics.

In the readition of the bestselling Chaos and A Brief History of Time, here is a science book with mainstream appeal. Proponents of artificial intelligence maintain that eventually a computer will be able to do everything a human mind can do, but Oxford University Professor of Mathematics Roger Penrose explains his view that there are facets of human thinking that can never be emulated by a machine. Drawings throughout.
Some love it, some hate it, but The Emperor's New Mind, physicist Roger Penrose's 1989 treatise attacking the foundations of strong artificial intelligence, is crucial for anyone interested in the history of thinking about AI and consciousness. Part survey of modern physics, part exploration of the philosophy of mind, the book is not for casual readers--though it's not overly technical, it rarely pauses to let the reader catch a breath. The overview of relativity and quantum theory, written by a master, is priceless and uncontroversial. The exploration of consciousness and AI, though, is generally considered as resting on shakier ground.
Penrose claims that there is an intimate, perhaps unknowable relation between quantum effects and our thinking, and ultimately derives his anti-AI stance from his proposition that some, if not all, of our thinking is non-algorithmic. Of course, these days we believe that there are other avenues to AI than traditional algorithmic programming; while he has been accused of setting up straw robots to knock down, this accusation is unfair. Little was then known about the power of neural networks and behavior-based robotics to simulate (and, some would say, produce) intelligent problem-solving behavior. Whether these tools will lead to strong AI is ultimately a question of belief, not proof, and The Emperor's New Mind offers powerful arguments useful to believer and nonbeliever alike. --Rob Lightner

Thirty-five years ago, C. P. Snow, in a now famous essay, wrote about the polarization of the "two cultures" -- literary intellectuals on the one hand, and scientists on the other. Although he hoped for the emergence of a "third culture" that would bridge the gap, it is only recently that science has changed the intellectual landscape.Brockman's thesis that science is emerging as the intellectual center of our society is brought to life vividly in "The Third Culture, " which weaves together the voices of some of today's most influential scientific figures, including: Stephen Jay Gould and Richard Dawkins on the implications of evolution Steven Pinker, Marvin Minsky, Daniel C. Dennett, and Roger Penrose on how the mind worksMurray Gell-Mann and Stuart Kauffman on the new sciences of complexity"The Third Culture" is an honest picture of science in action. It is at once stimulating, challenging, and riveting.

The eagerly anticipated updated resource on one of the most important areas of research and development: multi-agent systems Multi-agent systems allow many intelligent agents to interact with each other, and this field of study has advanced at a rapid pace since the publication of the first edition of this book, which was nearly a decade ago. With this exciting new edition, the coverage of multi-agents is completely updated to include several areas that have come to prominence in the last several years, including auctions, computational social choice, and markov decision processes. In turn, a variety of topics that were initially considered critical have dwindled in importance, so the coverage of that subject matter is decreased with this new edition. The result of this redefined balance of coverage is a timely and essential resource on a popular topic. Introduces you to the concept of agents and multi-agent systems and the main applications for which they are appropriate Discusses the main issues surrounding the design of intelligent agents and a multi-agent society Delves into a number of typical applications for agent technology Addresses deductive reasoning agents, practical reasoning agents, reactive and hybrid agents, and more Reviews multi-agent decision making, communication and cooperation, and intelligent autonomous agents By the end of the book, you will have a firm grasp on how agents are distinct from other software paradigms and understand the characteristics of applications that lend themselves to agent-oriented software.

Probabilistic robotics is a new and growing area in robotics, concerned with perception and control in the face of uncertainty. Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects.