Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory.All the essential topics in information theory are covered in detail, including entropy, data compression, channel capacity, rate distortion, network information theory, and hypothesis testing. The authors provide readers with a solid understanding of the underlying theory and applications. Problem sets and a telegraphic summary at the end of each chapter further assist readers. The historical notes that follow each chapter recap the main points.The Second Edition features: * Chapters reorganized to improve teaching * 200 new problems * New material on source coding, portfolio theory, and feedback capacity * Updated referencesNow current and enhanced, the Second Edition of Elements of Information Theory remains the ideal textbook for upper-level undergraduate and graduate courses in electrical engineering, statistics, and telecommunications.

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

    The authors provide precise definitions and full proofs of results, sacrificing generalities and limiting the scope of the material in order to do so. The text is organized in four parts: strategic games, extensive games with perfect information, extensive games with imperfect information, and coalitional games. It includes over 100 exercises. Solution ManualTable of Contents, Errata, and more...

    David Klatzow was the only independent forensic investigator in South Africa. During the apartheid years, a time of police brutality and state cover-ups, he was the man human rights lawyers called when they needed independent forensic evidence to uncover the truth. Although some cases are still unsolved, for him a case is never closed. The truth is out there, and he will find it.Klatzow's investigations into countless notorious cases, such as the Guguletu Seven, the Trojan Horse, the murders of human rights lawyer Bheki Mlangeni and activist Dr. David Webster, and the bombing of Khotso House and Cosatu House, made him a controversial public figure. Hampered by the apartheid police and the legal system, he was always fearless and earned a reputation of being an 'ANC supporter', even though he always remained impartial. On a non-political level, he was instrumental in changing the testing mechanism for drunk driving in the 1980s and became an expert in fire investigations.One of his most enduring interests is uncovering the truth behind the Helderberg airplane crash. Through a detailed analysis of the findings of the Margo Commission of Inquiry and having sifted through all available evidence, he is convinced that the official version of the story is far from the truth. More recently, Klatzow investigated the Paarl Press fire, the assassination of Brett Kebble and the murder of Inge Lotz. Fascinating reading for anyone interested in crime and current affairs; puts into perspective much of the information one hears about in the news.

    Mastering this art will not only make you the most desired developer in the market, but it will transform the craziest deadline into "Consider it done, Sir".

    Yet geometry is so much more than shapes and numbers; indeed, it governs much of our lives—from architecture and microchips to car design, animated movies, the molecules of food, even our own body chemistry. And as Siobhan Roberts elegantly conveys in The King of Infinite Space, there can be no better guide to the majesty of geometry than Donald Coxeter, perhaps the greatest geometer of the twentieth century.Many of the greatest names in intellectual history—Pythagoras, Plato, Archimedes, Euclid— were geometers, and their creativity and achievements illuminate those of Coxeter, revealing geometry to be a living, ever-evolving endeavor, an intellectual adventure that has always been a building block of civilization. Coxeter's special contributions—his famed Coxeter groups and Coxeter diagrams—have been called by other mathematicians "tools as essential as numbers themselves," but his greatest achievement was to almost single-handedly preserve the tradition of classical geometry when it was under attack in a mathematical era that valued all things austere and rational.Coxeter also inspired many outside the field of mathematics. Artist M. C. Escher credited Coxeter with triggering his legendary Circle Limit patterns, while futurist/inventor Buckminster Fuller acknowledged that his famed geodesic dome owed much to Coxeter's vision. The King of Infinite Space is an elegant portal into the fascinating, arcane world of geometry.

    This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

    It was a movement that embraced flower-power and psychedelic consciousness-expansion, that lionized Ho Chi Minh and Fidel Castro and launched the Black Panthers and the Theater of the Absurd.In Return Of The Primitive (originally published in 1971 as The New Left), Ayn Rand, bestselling novelist and originator of the theory of Objectivism, identified the intellectual roots of this movement. She urged people to repudiate its mindless nihilism and to uphold, instead, a philosophy of reason, individualism, capitalism, and technological progress.Editor Peter Schwartz, in this new, expanded version of The New Left, has reorganized Rand's essays and added some of his own in order to underscore the continuing relevance of her analysis of that period. He examines such current ideologies as feminism, environmentalism and multiculturalism and argues that the same primitive, tribalist, anti-industrial mentality which animated the New Left a generation ago is shaping society today.

    Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include: The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated.Carefully chosen advanced topics that can be skipped in a standard one-semester course, but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. In addition to the text, DasGupta also offers a Solutions Manual, which is available on the Online Learning Center.Algorithms is an outstanding undergraduate text, equally informed by the historical roots and contemporary applications of its subject. Like a captivating novel, it is a joy to read. Tim Roughgarden Stanford University

    This edition also features the developments in Operations Research, such as metaheuristics, simulation, and spreadsheet modeling.

    Republished in book form shortly thereafter, it has since gone through four hardcover and sixteen paperback printings. It is a revolutionary work, astounding in its foresight and contemporaneity. The University of Illinois Press is pleased and honored to issue this commemorative reprinting of a classic.

    This revised edition includes a CD-Rom with exercises that will help the student have a better understanding of equations, formulas, etc.