Download or read book Learning to Play the Game My Journey Through Silence written by Jonathan Kohlmeier and published by Lulu.com. This book was released on 2016-10-11 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Everyone has fears. A fear of the dark, a fear of heights, or even a fear of the unknown can make leading an otherwise normal life difficult. But what if you were afraid not of the dark or of heights-but of other people? What if you were overcome with paralyzing terror and even pushed to the brink of sickness each time you talked with another person-even though you wanted more than anything to be with and enjoy the company of that person? In Learning to Play the Game: My Journey through Silence, author Jonathan Kohlmeier shares a coming-of-age memoir of his young life living with selective mutism-an extreme form of social anxiety. At first as a child being so afraid that he could barely speak outside of the home, Jon's story of struggle turns triumph as he is eventually able to join the debate team in high school. From the start of his journey in kindergarten to his high school graduation, Jon chronicles his desire to be "normal"-whatever that means. 2018 Next Generation Indie Book Awards Finalist

Download or read book Learning the Game written by Kevin Waltman and published by Turtleback Books. This book was released on 2006-10-01 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: For use in schools and libraries only. When he and his high-school basketball teammates steal from a fraternity house in their small Indiana town, Nate contends with his guilt, his loyalty to his friends, and his desire to help his older brother who comes under suspicion for the crime.

Download or read book Deep Learning and the Game of Go written by Kevin Ferguson and published by Simon and Schuster. This book was released on 2019-01-06 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Deep Learning and the Game of Go teaches you how to apply the power of deep learning to complex reasoning tasks by building a Go-playing AI. After exposing you to the foundations of machine and deep learning, you'll use Python to build a bot and then teach it the rules of the game. Foreword by Thore Graepel, DeepMind Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning-based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can learn those same deep learning techniques by building your own Go bot! About the Book Deep Learning and the Game of Go introduces deep learning by teaching you to build a Go-winning bot. As you progress, you'll apply increasingly complex training techniques and strategies using the Python deep learning library Keras. You'll enjoy watching your bot master the game of Go, and along the way, you'll discover how to apply your new deep learning skills to a wide range of other scenarios! What's inside Build and teach a self-improving game AI Enhance classical game AI systems with deep learning Implement neural networks for deep learning About the Reader All you need are basic Python skills and high school-level math. No deep learning experience required. About the Author Max Pumperla and Kevin Ferguson are experienced deep learning specialists skilled in distributed systems and data science. Together, Max and Kevin built the open source bot BetaGo. Table of Contents PART 1 - FOUNDATIONS Toward deep learning: a machine-learning introduction Go as a machine-learning problem Implementing your first Go bot PART 2 - MACHINE LEARNING AND GAME AI Playing games with tree search Getting started with neural networks Designing a neural network for Go data Learning from data: a deep-learning bot Deploying bots in the wild Learning by practice: reinforcement learning Reinforcement learning with policy gradients Reinforcement learning with value methods Reinforcement learning with actor-critic methods PART 3 - GREATER THAN THE SUM OF ITS PARTS AlphaGo: Bringing it all together AlphaGo Zero: Integrating tree search with reinforcement learning

Download or read book Handbook of Game Based Learning written by Jan L. Plass and published by MIT Press. This book was released on 2020-02-04 with total page 601 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to the latest research and theory on learning and instruction with computer games. This book offers a comprehensive introduction to the latest research on learning and instruction with computer games. Unlike other books on the topic, which emphasize game development or best practices, Handbook of Game-Based Learning is based on empirical findings and grounded in psychological and learning sciences theory. The contributors, all leading researchers in the field, offer a range of perspectives, including cognitive, motivational, affective, and sociocultural. They explore research on whether (and how) computer games can help students learn educational content and academic skills; which game features (including feedback, incentives, adaptivity, narrative theme, and game mechanics) can improve the instructional effectiveness of these games; and applications, including games for learning in STEM disciplines, for training cognitive skills, for workforce learning, and for assessment. The Handbook offers an indispensable reference both for readers with practical interests in designing or selecting effective game-based learning environments and for scholars who conduct or evaluate research in the field. It can also be used in courses related to play, cognition, motivation, affect, instruction, and technology. Contributors Roger Azevedo, Ryan S. Baker, Daphne Bavelier, Amanda E. Bradbury, Ruth C. Clark, Michele D. Dickey, Hamadi Henderson, Bruce D. Homer, Fengfeng Ke, Younsu Kim, Charles E. Kinzer, Eric Klopfer, James C. Lester, Kristina Loderer, Richard E. Mayer, Bradford W. Mott, Nicholas V. Mudrick, Brian Nelson, Frank Nguyen, V. Elizabeth Owen, Shashank Pawar, Reinhard Pekrun, Jan L. Plass, Charles Raffale, Jonathon Reinhardt, C. Scott Rigby, Jonathan P. Rowe, Richard M. Ryan, Ruth N. Schwartz, Quinnipiac Valerie J. Shute, Randall D. Spain, Constance Steinkuehler, Frankie Tam, Michelle Taub, Meredith Thompson, Steven L. Thorne, A. M. Tsaasan

Download or read book Learning by Playing written by Fran Blumberg and published by Oxford University Press, USA. This book was released on 2014 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a growing recognition in the learning sciences that video games can no longer be seen as impediments to education, but rather, they can be developed to enhance learning. Educational and developmental psychologists, education researchers, media psychologists, and cognitive psychologists are now joining game designers and developers in seeking out new ways to use video game play in the classroom. In Learning by Playing, a diverse group of contributors provide perspectives on the most current thinking concerning the ramifications of leisure video game play for academic classroom learning. The first section of the text provides foundational understanding of the cognitive skills and content knowledge that children and adolescents acquire and refine during video game play. The second section explores game features that captivate and promote skills development among game players. The subsequent sections discuss children and adolescents' learning in the context of different types of games and the factors that contribute to transfer of learning from video game play to the classroom. These chapters then form the basis for the concluding section of the text: a specification of the most appropriate research agenda to investigate the academic potential of video game play, particularly using those games that child and adolescent players find most compelling. Contributors include researchers in education, learning sciences, and cognitive and developmental psychology, as well as instructional design researchers.

Download or read book The Circuit written by Francisco Jiménez and published by UNM Press. This book was released on 1997 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: A collection of stories about the life of a migrant family.

Download or read book Making Learning Whole written by David Perkins and published by John Wiley & Sons. This book was released on 2010-09-28 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: New in Paperback! Make learning more meaningful by teaching the "whole game" David Perkins, a noted authority on teaching and learning and co-director of Harvard's Project Zero, introduces a practical and research-based framework for teaching. He describes how teaching any subject at any level can be made more effective if students are introduced to the "whole game," rather than isolated pieces of a discipline. Perkins explains how learning academic subjects should be approached like learning baseball or any game, and he demonstrates this with seven principles for making learning whole: from making the game worth playing (emphasizing the importance of motivation to sustained learning), to working on the hard parts (the importance of thoughtful practice), to learning how to learn (developing self-managed learners). Vividly explains how to organize learning in ways that allow people to do important things with what they know Offers guidelines for transforming education to prepare our youth for success in a rapidly changing world Filled with real-world, illustrative examples of the seven principles At the end of each chapter, Perkins includes "Wonders of Learning," a summary of the key ideas.

Download or read book Buddy Holly written by Spencer Leigh and published by McNidder and Grace. This book was released on 2018-11-05 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Definitive account of Buddy Holly's life and career published to coincide with 60th anniversary of his death.

Download or read book Hands on Rust written by Herbert Wolverson and published by Pragmatic Bookshelf. This book was released on 2021-06-30 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rust is an exciting new programming language combining the power of C with memory safety, fearless concurrency, and productivity boosters - and what better way to learn than by making games. Each chapter in this book presents hands-on, practical projects ranging from "Hello, World" to building a full dungeon crawler game. With this book, you'll learn game development skills applicable to other engines, including Unity and Unreal. Rust is an exciting programming language combining the power of C with memory safety, fearless concurrency, and productivity boosters. With Rust, you have a shiny new playground where your game ideas can flourish. Each chapter in this book presents hands-on, practical projects that take you on a journey from "Hello, World" to building a full dungeon crawler game. Start by setting up Rust and getting comfortable with your development environment. Learn the language basics with practical examples as you make your own version of Flappy Bird. Discover what it takes to randomly generate dungeons and populate them with monsters as you build a complete dungeon crawl game. Run game systems concurrently for high-performance and fast game-play, while retaining the ability to debug your program. Unleash your creativity with magical items, tougher monsters, and intricate dungeon design. Add layered graphics and polish your game with style. What You Need: A computer running Windows 10, Linux, or Mac OS X.A text editor, such as Visual Studio Code.A video card and drivers capable of running OpenGL 3.2.

Download or read book What Video Games Have to Teach Us About Learning and Literacy Second Edition written by James Paul Gee and published by Macmillan. This book was released on 2014-12-02 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cognitive Development in a Digital Age James Paul Gee begins his classic book with "I want to talk about video games–yes, even violent video games–and say some positive things about them." With this simple but explosive statement, one of America's most well-respected educators looks seriously at the good that can come from playing video games. This revised edition expands beyond mere gaming, introducing readers to fresh perspectives based on games like World of Warcraft and Half-Life 2. It delves deeper into cognitive development, discussing how video games can shape our understanding of the world. An undisputed must-read for those interested in the intersection of education, technology, and pop culture, What Video Games Have to Teach Us About Learning and Literacy challenges traditional norms, examines the educational potential of video games, and opens up a discussion on the far-reaching impacts of this ubiquitous aspect of modern life.

Download or read book Learning to Play written by Aske Plaat and published by Springer Nature. This book was released on 2020-12-23 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this textbook the author takes as inspiration recent breakthroughs in game playing to explain how and why deep reinforcement learning works. In particular he shows why two-person games of tactics and strategy fascinate scientists, programmers, and game enthusiasts and unite them in a common goal: to create artificial intelligence (AI). After an introduction to the core concepts, environment, and communities of intelligence and games, the book is organized into chapters on reinforcement learning, heuristic planning, adaptive sampling, function approximation, and self-play. The author takes a hands-on approach throughout, with Python code examples and exercises that help the reader understand how AI learns to play. He also supports the main text with detailed pointers to online machine learning frameworks, technical details for AlphaGo, notes on how to play and program Go and chess, and a comprehensive bibliography. The content is class-tested and suitable for advanced undergraduate and graduate courses on artificial intelligence and games. It's also appropriate for self-study by professionals engaged with applications of machine learning and with games development. Finally it's valuable for any reader engaged with the philosophical implications of artificial and general intelligence, games represent a modern Turing test of the power and limitations of AI.

Download or read book Game based Learning Across the Disciplines written by Carmela Aprea and published by Springer Nature. This book was released on 2021-08-02 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volume focuses on epistemological, theoretical and empirical issues of game-based learning in various disciplines. It encompasses questions of game design as well as instructional integration and organizational implementation of game-based learning across various disciplines and includes contributions from different levels of the formal educational system (i.e., primary, secondary and tertiary education) as well as contributions reporting the use of game-based learning in informal learning settings. The volume addresses scholars, practitioners and students who are interested in how games and game-based learning can be designed, implemented and evaluated in a cross-, inter- and transdisciplinary perspective.

Download or read book Resonant Games written by Eric Klopfer and published by MIT Press. This book was released on 2018-07-17 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Principles for designing educational games that integrate content and play and create learning experiences connecting to many areas of learners' lives. Too often educational videogames are narrowly focused on specific learning outcomes dictated by school curricula and fail to engage young learners. This book suggests another approach, offering a guide to designing games that integrates content and play and creates learning experiences that connect to many areas of learners' lives. These games are not gamified workbooks but are embedded in a long-form experience of exploration, discovery, and collaboration that takes into consideration the learning environment. Resonant Games describes twenty essential principles for designing games that offer this kind of deeper learning experience, presenting them in connection with five games or collections of games developed at MIT's educational game research lab, the Education Arcade. Each of the games—which range from Vanished, an alternate reality game for middle schoolers promoting STEM careers, to Ubiquitous Bio, a series of casual mobile games for high school biology students—has a different story, but all spring from these fundamental assumptions: honor the whole learner, as a full human being, not an empty vessel awaiting a fill-up; honor the sociality of learning and play; honor a deep connection between the content and the game; and honor the learning context—most often the public school classroom, but also beyond the classroom.

Download or read book Hands On Reinforcement Learning for Games written by Micheal Lanham and published by Packt Publishing Ltd. This book was released on 2020-01-03 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore reinforcement learning (RL) techniques to build cutting-edge games using Python libraries such as PyTorch, OpenAI Gym, and TensorFlow Key FeaturesGet to grips with the different reinforcement and DRL algorithms for game developmentLearn how to implement components such as artificial agents, map and level generation, and audio generationGain insights into cutting-edge RL research and understand how it is similar to artificial general researchBook Description With the increased presence of AI in the gaming industry, developers are challenged to create highly responsive and adaptive games by integrating artificial intelligence into their projects. This book is your guide to learning how various reinforcement learning techniques and algorithms play an important role in game development with Python. Starting with the basics, this book will help you build a strong foundation in reinforcement learning for game development. Each chapter will assist you in implementing different reinforcement learning techniques, such as Markov decision processes (MDPs), Q-learning, actor-critic methods, SARSA, and deterministic policy gradient algorithms, to build logical self-learning agents. Learning these techniques will enhance your game development skills and add a variety of features to improve your game agent’s productivity. As you advance, you’ll understand how deep reinforcement learning (DRL) techniques can be used to devise strategies to help agents learn from their actions and build engaging games. By the end of this book, you’ll be ready to apply reinforcement learning techniques to build a variety of projects and contribute to open source applications. What you will learnUnderstand how deep learning can be integrated into an RL agentExplore basic to advanced algorithms commonly used in game developmentBuild agents that can learn and solve problems in all types of environmentsTrain a Deep Q-Network (DQN) agent to solve the CartPole balancing problemDevelop game AI agents by understanding the mechanism behind complex AIIntegrate all the concepts learned into new projects or gaming agentsWho this book is for If you’re a game developer looking to implement AI techniques to build next-generation games from scratch, this book is for you. Machine learning and deep learning practitioners, and RL researchers who want to understand how to use self-learning agents in the game domain will also find this book useful. Knowledge of game development and Python programming experience are required.

Download or read book Play to Learn written by Sharon Boller and published by Association for Talent Development. This book was released on 2017-03-03 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: When trainers use games, learners win big. As a trainer interested in game design, you know that games are more effective than lectures. You've seen firsthand how immersive games hold learners' interest, helping them explore new skills and experience different points of view. But how do you become the Milton Bradley of learning games? Play to Learn is here to help. This book bridges the gap between instructional design and game design; it's written to grow your game literacy and strengthen crucial game design skills. Experts Sharon Boller and Karl Kapp share real examples of in-person and online games, and offer an online game for you to try as you read. They walk you through evaluating entertainment and learning games, so you can apply the best to your own designs. Play to Learn will also show you how to: Link game design to your business needs and learning objectives. Test your prototype and refine your design. Deploy your game to motivated and excited learners. So don't just play around. Think big, design well, and use Play to Learn as your guide.

Download or read book The Real Estate Game written by William J Poorvu and published by Simon and Schuster. This book was released on 1999-09-13 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: From a Harvard Business School professor comes a concise, accessible, state-of-the-art guide to developing and investing in real estate.

Download or read book Prediction Learning and Games written by Nicolo Cesa-Bianchi and published by Cambridge University Press. This book was released on 2006-03-13 with total page 4 pages. Available in PDF, EPUB and Kindle. Book excerpt: This important text and reference for researchers and students in machine learning, game theory, statistics and information theory offers a comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of individual sequences does not impose any probabilistic assumption on the data-generating mechanism. Yet, prediction algorithms can be constructed that work well for all possible sequences, in the sense that their performance is always nearly as good as the best forecasting strategy in a given reference class. The central theme is the model of prediction using expert advice, a general framework within which many related problems can be cast and discussed. Repeated game playing, adaptive data compression, sequential investment in the stock market, sequential pattern analysis, and several other problems are viewed as instances of the experts' framework and analyzed from a common nonstochastic standpoint that often reveals new and intriguing connections.