Addressing a field that has been dominated by astronomers, physicists, engineers, and computer scientists, the contributors to this collection raise questions that may have been overlooked by physical scientists about the ease of establishing meaningful communication with an extraterrestrial intelligence. These scholars are grappling with some of the enormous challenges that will face humanity if an information-rich signal emanating from another world is detected. By drawing on issues at the core of contemporary archaeology and anthropology, we can be much better prepared for contact with an extraterrestrial civilization, should that day ever come.
The past decade has delivered remarkable discoveries in the study of exoplanets. Hand-in-hand with these advances, a theoretical understanding of the myriad of processes that dictate the formation and evolution of planets has matured, spurred on by the avalanche of unexpected discoveries. Appreciation of the factors that make a planet hospitable to life has grown in sophistication, as has understanding of the context for biosignatures, the remotely detectable aspects of a planet's atmosphere or surface that reveal the presence of life. Exoplanet Science Strategy highlights strategic priorities for large, coordinated efforts that will support the scientific goals of the broad exoplanet science community. This report outlines a strategic plan that will answer lingering questions through a combination of large, ambitious community-supported efforts and support for diverse, creative, community-driven investigator research.
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 the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
NATIONAL BESTSELLER • From one of the world’s leading physicists and author of the Pulitzer Prize finalist The Elegant Universe, comes “an astonishing ride” through the universe (The New York Times) that makes us look at reality in a completely different way. Space and time form the very fabric of the cosmos. Yet they remain among the most mysterious of concepts. Is space an entity? Why does time have a direction? Could the universe exist without space and time? Can we travel to the past? Greene has set himself a daunting task: to explain non-intuitive, mathematical concepts like String Theory, the Heisenberg Uncertainty Principle, and Inflationary Cosmology with analogies drawn from common experience. From Newton’s unchanging realm in which space and time are absolute, to Einstein’s fluid conception of spacetime, to quantum mechanics’ entangled arena where vastly distant objects can instantaneously coordinate their behavior, Greene takes us all, regardless of our scientific backgrounds, on an irresistible and revelatory journey to the new layers of reality that modern physics has discovered lying just beneath the surface of our everyday world.
This textbook reflects its authors' experiences both as faculty members who have taught the introductory psychology course several dozen times, and, earlier, as students whose own interest in psychology was sparked by instructors who brought the introductory course to life. The text's flexible organizing framework (Levels of Analysis), depth of research, emphasis on critical thinking, and engaging writing help instructors convey the expanse and excitement of the field of psychology, while maintaining scientific rigor. The new third edition features a separate chapter on intelligence, chapter reorganizations, and updated research throughout.
In recent years, several new concepts have emerged in the field of stratospheric ozone depletion, creating a need for a concise in-depth publication covering the ozone-climate issue. This monograph fills that void in the literature and gives detailed treatment of recent advances in the field of stratospheric ozone depletion. It puts particular emphasis on the coupling between changes in the ozone layer and atmospheric change caused by a changing climate. The book, written by leading experts in the field, brings the reader the most recent research in this area and fills the gap between advanced textbooks and assessments.
Before Palm Pilots and iPods, PCs and laptops, the term "computer" referred to the people who did scientific calculations by hand. These workers were neither calculating geniuses nor idiot savants but knowledgeable people who, in other circumstances, might have become scientists in their own right. When Computers Were Human represents the first in-depth account of this little-known, 200-year epoch in the history of science and technology. Beginning with the story of his own grandmother, who was trained as a human computer, David Alan Grier provides a poignant introduction to the wider world of women and men who did the hard computational labor of science. His grandmother's casual remark, "I wish I'd used my calculus," hinted at a career deferred and an education forgotten, a secret life unappreciated; like many highly educated women of her generation, she studied to become a human computer because nothing else would offer her a place in the scientific world. The book begins with the return of Halley's comet in 1758 and the effort of three French astronomers to compute its orbit. It ends four cycles later, with a UNIVAC electronic computer projecting the 1986 orbit. In between, Grier tells us about the surveyors of the French Revolution, describes the calculating machines of Charles Babbage, and guides the reader through the Great Depression to marvel at the giant computing room of the Works Progress Administration. When Computers Were Human is the sad but lyrical story of workers who gladly did the hard labor of research calculation in the hope that they might be part of the scientific community. In the end, they were rewarded by a new electronic machine that took the place and the name of those who were, once, the computers.
Learn all about implementing a good gamification design into your products, workplace, and lifestyle Key FeaturesExplore what makes a game fun and engagingGain insight into the Octalysis Framework and its applicationsDiscover the potential of the Core Drives of gamification through real-world scenariosBook Description Effective gamification is a combination of game design, game dynamics, user experience, and ROI-driving business implementations. This book explores the interplay between these disciplines and captures the core principles that contribute to a good gamification design. The book starts with an overview of the Octalysis Framework and the 8 Core Drives that can be used to build strategies around the various systems that make games engaging. As the book progresses, each chapter delves deep into a Core Drive, explaining its design and how it should be used. Finally, to apply all the concepts and techniques that you learn throughout, the book contains a brief showcase of using the Octalysis Framework to design a project experience from scratch. After reading this book, you'll have the knowledge and skills to enable the widespread adoption of good gamification and human-focused design in all types of industries. What you will learnDiscover ways to use gamification techniques in real-world situationsDesign fun, engaging, and rewarding experiences with OctalysisUnderstand what gamification means and how to categorize itLeverage the power of different Core Drives in your applicationsExplore how Left Brain and Right Brain Core Drives differ in motivation and design methodologiesExamine the fascinating intricacies of White Hat and Black Hat Core DrivesWho this book is for Anyone who wants to implement gamification principles and techniques into their products, workplace, and lifestyle will find this book useful.
