He had, therefore, full opportunities of seeing the country and its life from various points of view. He has utilized his observations in an entertaining book. It is not — and does not pretend lo be — a scientific work, or technical in any sense. It gives, however, an excellent idea of conditions and ways of living in the Klondike at all seasons, and of the hardships which the pioneers had to undergo. Nothing but gold — the prospect of wealth — could induce men to live in such a climate, and to combat the many difficulties which it entails. Mr. Lynch, a Californian of means and position, arrived at Dawson in the summer of 1898. As the first discoveries of gold in the Klondike valley were made in August of 1896, Mr. Lynch found a mining town not two years old, unpaved and insanitary, crowded with adventurers of every nation, in fact still a typical “ tough" mining-camp, except that lawlessness and crime were sternly repressed by the vigilant Mounted Police. He spent the following winter in the town, making expeditions to the gold-bearing creeks, examining mines and studying the methods of working them. Early in the spring of 1899 he bought a claim which he believed would repay him and set himself at once to develop it thoroughly. During his stay he had seen Dawson transformed into a paved, sewaged, well built, well lighted city, and the streets, no longer thronged with rough-mannered miners and adventurers, had become the promenade of well dressed business men and ladies (real ladies !) intent on shopping. As one of the earliest of the new species of Klondike miner, he is able to give an account of the transition that took place, largely owing to the enterprise of men of his own stamp, and the book is an interesting addition to Klondike literature. Mr. Lynch's narrative is plainly written, in a way which leads one to believe in its substantial truth. It reads well, and brings out many points which will interest the miner, as well as the casual reader. He had confidence in the future of the country, and believed that it would hold a large population for many years, in spite of the drawbacks of climate.

    In reality, he writes, “the lobster fisherman is caught up in a thick and complex web of social relationships. Survival in the industry depends as much on the ability to manipulate social relationships as on technical skills.” Acheson replaces our romantic image of the lobsterman with descriptions of the highly territorial and hierarchical “harbor gangs,” daily and annual cycles of lobstering, intricacies of marketing the catch, and the challenge of managing a communal resource.

    This book offers a unique insight into how crews responded to crisis and what really happened.

    With the stock market sinking and soaring from day to day, retirement plans becoming less certain, and a longer life expectancy in retirement, more people are looking for some control over their investments. If you're one of them, Investing Online For Dummies, 6th Edition might be just what you're looking for. The Internet brings a world of investment resources to your desktop, but how do you find your way through the dizzying array of investment possibilities? The Dummies Way, of course! This book helps you set reasonable expectations, assess your risk tolerance, choose an asset allocation, analyze and select investments, and maximize your financial success. You'll discover how toDetermine how much you can afford to invest Choose an online broker Research, trade, and track investments online Measure the potential return of a stock Maximize your investment knowledge and build a profitable portfolio Buy bonds online Understand options, commodities, and IPOs If you've decided to take control of your investments but don't want to make it your full-time job, Investing Online For Dummies, 6th Edition gives you the important information that will also give you confidence. Completely updated to cover all the new online tools and resources, it even provides some bonus assistance on the companion Web site.

    Known for its carefully developed, thoroughly integrated, step-by-step approach to problem solving, General Chemistry helps students master quantitative skills and build a lasting conceptual understanding of key chemical concepts. The Ninth Edition retains this hallmark approach and builds upon the conceptual focus through key new features and revisions.

    One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.

    This connectedness is found in many incarnations: in the rapid growth of the Internet, in the ease with which global communication takes place, and in the ability of news and information as well as epidemics and financial crises to spread with surprising speed and intensity. These are phenomena that involve networks, incentives, and the aggregate behavior of groups of people; they are based on the links that connect us and the ways in which our decisions can have subtle consequences for others. This introductory undergraduate textbook takes an interdisciplinary look at economics, sociology, computing and information science, and applied mathematics to understand networks and behavior. It describes the emerging field of study that is growing at the interface of these areas, addressing fundamental questions about how the social, economic, and technological worlds are connected.

    The book drives to the heart of the exciting debate on the origins of life and maintenance of order in complex biological systems. It focuses on the concept of self-organization: the spontaneous emergence of order that is widely observed throughout nature Kauffman argues that self-organization plays an important role in the Darwinian process of natural selection. Yet until now no systematic effort has been made to incorporate the concept of self-organization into evolutionary theory. The construction requirements which permit complex systems to adapt are poorly understood, as is the extent to which selection itself can yield systems able to adapt more successfully. This book explores these themes. It shows how complex systems, contrary to expectations, can spontaneously exhibit stunning degrees of order, and how this order, in turn, is essential for understanding the emergence and development of life on Earth. Topics include the new biotechnology of applied molecular evolution, with its important implications for developing new drugs and vaccines; the balance between order and chaos observed in many naturally occurring systems; new insights concerning the predictive power of statistical mechanics in biology; and other major issues. Indeed, the approaches investigated here may prove to be the new center around which biological science itself will evolve. The work is written for all those interested in the cutting edge of research in the life sciences.

    The analytic material is accompanied by many applications, examples, and exercises. The theory of noncooperative games studies the behavior of agents in any situation where each agent's optimal choice may depend on a forecast of the opponents' choices. "Noncooperative" refers to choices that are based on the participant's perceived selfinterest. Although game theory has been applied to many fields, Fudenberg and Tirole focus on the kinds of game theory that have been most useful in the study of economic problems. They also include some applications to political science. The fourteen chapters are grouped in parts that cover static games of complete information, dynamic games of complete information, static games of incomplete information, dynamic games of incomplete information, and advanced topics.--mitpress.mit.edu

    Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

    This work includes differential forms and the elegant forms of Maxwell's equations, and a chapter on probability and statistics. It also illustrates and proves mathematical relations.

    This edition contains NEW tables on Properties of Ionic Liquids, Solubilities of Hydrocarbons in Sea Water, Solubility of Organic Compounds in Superheated Water, and Nutritive Value of Foods. It also updates many tables including Critical Constants, Heats of Vaporization, Aqueous Solubility of Organic Compounds, Vapor Pressure of Mercury, Scientific Abbreviations and Symbols, and Bond Dissociation Energies. The 88th Edition also presents a new Foreword written by Dr. Harold Kroto, a 1996 Nobel Laureate in Chemistry.

    A number of the key figures in the new edition are revised to provide a more inviting and informative treatment. The figures are broken into component parts with supporting commentary so that they can more readily see the key ideas. Material from The Flying Circus is incorporated into the chapter opener puzzlers, sample problems, examples and end-of-chapter problems to make the subject more engaging. Checkpoints enable them to check their understanding of a question with some reasoning based on the narrative or sample problem they just read. Sample Problems also demonstrate how engineers can solve problems with reasoned solutions.

    His Incompleteness Theorem turned not only mathematics but also the whole world of science and philosophy on its head. Equally legendary were Gö's eccentricities, his close friendship with Albert Einstein, and his paranoid fear of germs that eventually led to his death from self-starvation. Now, in the first popular biography of this strange and brilliant thinker, John Casti and Werner DePauli bring the legend to life. After describing his childhood in the Moravian capital of Brno, the authors trace the arc of Gö's remarkable career, from the famed Vienna Circle, where philosophers and scientists debated notions of truth, to the Institute for Advanced Study in Princeton, New Jersey, where he lived and worked until his death in 1978. In the process, they shed light on Gö's contributions to mathematics, philosophy, computer science, artificial intelligence -- even cosmology -- in an entertaining and accessible way.

    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.