Introduction

Ready to write your book? So why haven’t you done it yet? If you’re like most nonfiction authors, fears are holding you back. Sound familiar? Is my idea good enough? How do I structure a book? What exactly are the steps to write it? How do I stay motivated? What if I actually finish it, and it’s bad? Worst of all: what if I publish it, and no one cares? How do I know if I’m even doing the right things? The truth is, writing a book can be scary and overwhelming—but it doesn’t have to be. There’s a way to know you’re on the right path and taking the right steps. How? By using a method that’s been validated with thousands of other Authors just like you. In fact, it’s the same exact process used to produce dozens of big bestsellers–including David Goggins’s Can’t Hurt Me, Tiffany Haddish’s The Last Black Unicorn, and Joey Coleman’s Never Lose a Customer Again. The Scribe Method is the tested and proven process that will help you navigate the entire book-writing process from start to finish–the right way. Written by 4x New York Times Bestselling Author Tucker Max and publishing expert Zach Obront, you’ll learn the step-by-step method that has helped over 1,500 authors write and publish their books. Now a Wall Street Journal Bestseller itself, The Scribe Method is specifically designed for business leaders, personal development gurus, entrepreneurs, and any expert in their field who has accumulated years of hard-won knowledge and wants to put it out into the world. Forget the rest of the books written by pretenders. This is the ultimate resource for anyone who wants to professionally write a great nonfiction book.

The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. 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 while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.

This is a comprehensive introduction to books and print culture which examines the move from the spoken word to written texts, the book as commodity, the power and profile of readers, and the future of the book in an electronic age.

Since the publication of the first edition of this book, the area of mathematical finance has grown rapidly, with financial analysts using more sophisticated mathematical concepts, such as stochastic integration, to describe the behavior of markets and to derive computing methods. Maintaining the lucid style of its popular predecessor, this concise and accessible introduction covers the probabilistic techniques required to understand the most widely used financial models. Along with additional exercises, this edition presents fully updated material on stochastic volatility models and option pricing as well as a new chapter on credit risk modeling. It contains many numerical experiments and real-world examples taken from the authors' own experiences. The book also provides all of the necessary stochastic calculus theory and implements some of the algorithms using SciLab. Key topics covered include martingales, arbitrage, option pricing, and the Black-Scholes model.

This book grew out of lecture notes I used in a course on difference equations that I taught at Trinity University for the past five years. The classes were largely pop ulated by juniors and seniors majoring in Mathematics, Engineering, Chemistry, Computer Science, and Physics. This book is intended to be used as a textbook for a course on difference equations at the level of both advanced undergraduate and beginning graduate. It may also be used as a supplement for engineering courses on discrete systems and control theory. The main prerequisites for most of the material in this book are calculus and linear algebra. However, some topics in later chapters may require some rudiments of advanced calculus. Since many of the chapters in the book are independent, the instructor has great flexibility in choosing topics for the first one-semester course. A diagram showing the interdependence of the chapters in the book appears following the preface. This book presents the current state of affairs in many areas such as stability, Z-transform, asymptoticity, oscillations and control theory. However, this book is by no means encyclopedic and does not contain many important topics, such as Numerical Analysis, Combinatorics, Special functions and orthogonal polyno mials, boundary value problems, partial difference equations, chaos theory, and fractals. The nonselection of these topics is dictated not only by the limitations imposed by the elementary nature of this book, but also by the research interest (or lack thereof) of the author.

This book is an introduction to singularities for graduate students and researchers. It is said that algebraic geometry originated in the seventeenth century with the famous work Discours de la méthode pour bien conduire sa raison, et chercher la vérité dans les sciences by Descartes. In that book he introduced coordinates to the study of geometry. After its publication, research on algebraic varieties developed steadily. Many beautiful results emerged in mathematicians’ works. Most of them were about non-singular varieties. Singularities were considered “bad” objects that interfered with knowledge of the structure of an algebraic variety. In the past three decades, however, it has become clear that singularities are necessary for us to have a good description of the framework of varieties. For example, it is impossible to formulate minimal model theory for higher-dimensional cases without singularities. Another example is that the moduli spaces of varieties have natural compactification, the boundaries of which correspond to singular varieties. A remarkable fact is that the study of singularities is developing and people are beginning to see that singularities are interesting and can be handled by human beings. This book is a handy introduction to singularities for anyone interested in singularities. The focus is on an isolated singularity in an algebraic variety. After preparation of varieties, sheaves, and homological algebra, some known results about 2-dim ensional isolated singularities are introduced. Then a classification of higher-dimensional isolated singularities is shown according to plurigenera and the behavior of singularities under a deformation is studied.

This book has been replaced by Introduction to Addictive Behaviors, Fifth Edition, ISBN 978-1-4625-3922-2.

Bridge the gap between research and practice with Introduction to Research: Understanding and Applying Multiple Strategies, 5th Edition. This easy-to-read edition covers all the major research design strategies: qualitative, quantitative, naturalistic, experimental-type, and mixed method. And with the text’s up-to-date research information and references, you will have a solid foundation from which to critique and understand research designs and their applications to healthcare and human service settings. Case examples provide real-life snapshots of what it is like to participate in different types of research processes, identify research dilemmas relevant to chapter subjects, and alert you to problems you might encounter. Authors make the topics more accessible, so research becomes more relevant - and topics come to life. Covers experimental-type, naturalistic, and mixed method design strategies to improve your ability to compare, contrast, and integrate different methods. Presents complex information clearly in a highly readable, and easy-to-understand, manner. Includes detailed discussions of qualitative and quantitative methodologies, a unique and balanced focus that makes this text more comprehensive than others in its field. NEW! Up-to-date research methods, strategies, and references, like digital sources, visual methods, and geographical analysis, give you the latest information on research in diverse areas of health and human services.