Make it! Code it! Break it! Mod it! Meg Ray's CODE THIS GAME! is a nonfiction visual guide, illustrated by Keith Zoo, that teaches young readers, 10-14, how to program and create their very own video game. Each chapter introduces key coding concepts as kids build an action strategy game in Python, an open-source programming language. The book features an innovative stand-up format that allows kids to read, program, and play their game simultaneously. With easy-to-follow step-by-step instructions, CODE THIS GAME! teaches kids to build a strategy action game called “Attack of the Vampire Pizzas!” The book also teaches how to modify the game and follow one's imagination by incorporating downloadable art assets. By the time kids finish the book, they'll have mastered basic coding concepts and created a personalized game.

Read, clap, and sing in 4/4 time! Count the beats like a conductor with the adorable animals in the marching band. Get your baby smiling and clapping along with you as you discover a love of music together! Clap on the first syllable of each word—and don’t let go until the word is done. Before long, you’ll be clapping to the marching beat. In BABY BEATS: LET'S LEARN 4/4 TIME, you’ll love to: - Engage young readers with hands-on interaction, percussion, and song - Build baby’s vocabulary by connecting words with illustrations - Stimulate baby through multisensory reading experiences - Inspire the love of conducting music for ages to come Play conductor in other time signatures with the BABY BEATS series: LET'S LEARN 3/4 TIME and LET'S LEARN 2/4 TIME!

The biggest challenge facing many game programmers is completing their game. Most game projects fizzle out, overwhelmed by the complexity of their own code. Game Programming Patterns tackles that exact problem. Based on years of experience in shipped AAA titles, this book collects proven patterns to untangle and optimize your game, organized as independent recipes so you can pick just the patterns you need. You will learn how to write a robust game loop, how to organize your entities using components, and take advantage of the CPUs cache to improve your performance. You'll dive deep into how scripting engines encode behavior, how quadtrees and other spatial partitions optimize your engine, and how other classic design patterns can be used in games.

Invent Your Own Computer Games with Python will teach you how to make computer games using the popular Python programming language—even if you’ve never programmed before! Begin by building classic games like Hangman, Guess the Number, and Tic-Tac-Toe, and then work your way up to more advanced games, like a text-based treasure hunting game and an animated collision-dodging game with sound effects. Along the way, you’ll learn key programming and math concepts that will help you take your game programming to the next level. Learn how to: –Combine loops, variables, and flow control statements into real working programs –Choose the right data structures for the job, such as lists, dictionaries, and tuples –Add graphics and animation to your games with the pygame module –Handle keyboard and mouse input –Program simple artificial intelligence so you can play against the computer –Use cryptography to convert text messages into secret code –Debug your programs and find common errors As you work through each game, you’ll build a solid foundation in Python and an understanding of computer science fundamentals. What new game will you create with the power of Python? The projects in this book are compatible with Python 3.

How culture uses games and how games use culture: an examination of Latin America's gaming practices and the representation of the region's cultures in games. Video games are becoming an ever more ubiquitous element of daily life, played by millions on devices that range from smart phones to desktop computers. An examination of this phenomenon reveals that video games are increasingly being converted into cultural currency. For video game designers, culture is a resource that can be incorporated into games; for players, local gaming practices and specific social contexts can affect their playing experiences. In Cultural Code, Phillip Penix-Tadsen shows how culture uses games and how games use culture, looking at examples related to Latin America. Both static code and subjective play have been shown to contribute to the meaning of games; Penix-Tadsen introduces culture as a third level of creating meaning. Penix-Tadsen focuses first on how culture uses games, looking at the diverse practices of play in Latin America, the ideological and intellectual uses of games, and the creative and economic possibilities opened up by video games in Latin America—the evolution of regional game design and development. Examining how games use culture, Penix-Tadsen discusses in-game cultural representations of Latin America in a range of popular titles (pointing out, for example, appearances of Rio de Janeiro's Christ the Redeemer statue in games from Call of Duty to the tourism-promoting Brasil Quest). He analyzes this through semiotics, the signifying systems of video games and the specific signifiers of Latin American culture; space, how culture is incorporated into different types of game environments; and simulation, the ways that cultural meaning is conveyed procedurally and algorithmically through gameplay mechanics.

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

With its unique focus on video game engines, the data-driven architectures of game development and play, this innovative textbook examines the impact of software on everyday life and explores the rise of engine-driven culture. Through a series of case studies, Eric Freedman lays out a clear methodology for studying the game development pipeline, and uses the video game engine as a pathway for media scholars and practitioners to navigate the complex terrain of software practice. Examining several distinct software ecosystems that include the proprietary efforts of Amazon, Apple, Capcom, Epic Games and Unity Technologies, and the unique ways that game engines are used in non-game industries, Freedman illustrates why engines matter. The studies bind together designers and players, speak to the labors of the game industry, value the work of both global and regional developers, and establish critical connection points between software and society. Freedman has crafted a much-needed entry point for students new to code, and a research resource for scholars and teachers working in media industries, game development and new media.