Deep Learning In Gaming And Animations

Author : Vikas Chaudhary,Moolchand Sharma,Prerna Sharma,Deevyankar Agarwal
Publisher : CRC Press
Page : 180 pages
File Size : 46,5 Mb
Release : 2021-12-07
Category : Computers
ISBN : 9781000504378

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Deep Learning in Gaming and Animations by Vikas Chaudhary,Moolchand Sharma,Prerna Sharma,Deevyankar Agarwal Pdf

Over the last decade, progress in deep learning has had a profound and transformational effect on many complex problems, including speech recognition, machine translation, natural language understanding, and computer vision. As a result, computers can now achieve human-competitive performance in a wide range of perception and recognition tasks. Many of these systems are now available to the programmer via a range of so-called cognitive services. More recently, deep reinforcement learning has achieved ground-breaking success in several complex challenges. This book makes an enormous contribution to this beautiful, vibrant area of study: an area that is developing rapidly both in breadth and depth. Deep learning can cope with a broader range of tasks (and perform those tasks to increasing levels of excellence). This book lays a good foundation for the core concepts and principles of deep learning in gaming and animation, walking you through the fundamental ideas with expert ease. This book progresses in a step-by-step manner. It reinforces theory with a full-fledged pedagogy designed to enhance students' understanding and offer them a practical insight into its applications. Also, some chapters introduce and cover novel ideas about how artificial intelligence (AI), deep learning, and machine learning have changed the world in gaming and animation. It gives us the idea that AI can also be applied in gaming, and there are limited textbooks in this area. This book comprehensively addresses all the aspects of AI and deep learning in gaming. Also, each chapter follows a similar structure so that students, teachers, and industry experts can orientate themselves within the text. There are few books in the field of gaming using AI. Deep Learning in Gaming and Animations teaches you how to apply the power of deep learning to build complex reasoning tasks. After being exposed to the foundations of machine and deep learning, you will use Python to build a bot and then teach it the game's rules. This book also focuses on how different technologies have revolutionized gaming and animation with various illustrations.

Author : Vikas Chaudhary,Moolchand Sharma,Prerna Sharma,Deevyankar Agarwal
Publisher : CRC Press
Page : 177 pages
File Size : 51,7 Mb
Release : 2021-12-07
Category : Computers
ISBN : 9781000504347

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Deep Learning in Gaming and Animations by Vikas Chaudhary,Moolchand Sharma,Prerna Sharma,Deevyankar Agarwal Pdf

Over the last decade, progress in deep learning has had a profound and transformational effect on many complex problems, including speech recognition, machine translation, natural language understanding, and computer vision. As a result, computers can now achieve human-competitive performance in a wide range of perception and recognition tasks. Many of these systems are now available to the programmer via a range of so-called cognitive services. More recently, deep reinforcement learning has achieved ground-breaking success in several complex challenges. This book makes an enormous contribution to this beautiful, vibrant area of study: an area that is developing rapidly both in breadth and depth. Deep learning can cope with a broader range of tasks (and perform those tasks to increasing levels of excellence). This book lays a good foundation for the core concepts and principles of deep learning in gaming and animation, walking you through the fundamental ideas with expert ease. This book progresses in a step-by-step manner. It reinforces theory with a full-fledged pedagogy designed to enhance students' understanding and offer them a practical insight into its applications. Also, some chapters introduce and cover novel ideas about how artificial intelligence (AI), deep learning, and machine learning have changed the world in gaming and animation. It gives us the idea that AI can also be applied in gaming, and there are limited textbooks in this area. This book comprehensively addresses all the aspects of AI and deep learning in gaming. Also, each chapter follows a similar structure so that students, teachers, and industry experts can orientate themselves within the text. There are few books in the field of gaming using AI. Deep Learning in Gaming and Animations teaches you how to apply the power of deep learning to build complex reasoning tasks. After being exposed to the foundations of machine and deep learning, you will use Python to build a bot and then teach it the game's rules. This book also focuses on how different technologies have revolutionized gaming and animation with various illustrations.

Author : Mark Liu
Publisher : CRC Press
Page : 465 pages
File Size : 55,7 Mb
Release : 2023-10-30
Category : Computers
ISBN : 9781000964776

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Machine Learning, Animated by Mark Liu Pdf

The release of ChatGPT has kicked off an arms race in Machine Learning (ML), however ML has also been described as a black box and very hard to understand. Machine Learning, Animated eases you into basic ML concepts and summarizes the learning process in three words: initialize, adjust and repeat. This is illustrated step by step with animation to show how machines learn: from initial parameter values to adjusting each step, to the final converged parameters and predictions. This book teaches readers to create their own neural networks with dense and convolutional layers, and use them to make binary and multi-category classifications. Readers will learn how to build deep learning game strategies and combine this with reinforcement learning, witnessing AI achieve super-human performance in Atari games such as Breakout, Space Invaders, Seaquest and Beam Rider. Written in a clear and concise style, illustrated with animations and images, this book is particularly appealing to readers with no background in computer science, mathematics or statistics. Access the book's repository at: https://github.com/markhliu/MLA

Author : John David Funge
Publisher : CRC Press
Page : 288 pages
File Size : 43,9 Mb
Release : 1999-07-22
Category : Computers
ISBN : 9781439864012

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AI for Games and Animation by John David Funge Pdf

John Funge introduces a new approach to creating autonomous characters. Cognitive modeling provides computer-animated characters with logic, reasoning, and planning skills. Individual chapters in the book provide concrete examples of advanced character animation, automated cinematography, and a real-time computer game. Source code, animations, imag

Author : Mark H. Liu
Publisher : Unknown
Page : 0 pages
File Size : 50,5 Mb
Release : 2023-12
Category : COMPUTERS
ISBN : 1003441289

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Machine Learning, Animated by Mark H. Liu Pdf

The release of ChatGPT has kicked off an arms race in Machine Learning (ML), however ML has also been described as a black box and very hard to understand. Machine Learning, Animatedeases you into basic ML concepts and summarizes the learning process in three words: initialize, adjust and repeat. This is illustrated step by step with animation to show how machines learn: from initial parameter values to adjusting each step, to the final converged parameters and predictions. This book teaches readers to create their own neural networks with dense and convolutional layers, and use them to make binary and multi-category classifications. Readers will learn how to build deep learning game strategies and combine this with reinforcement learning, witnessing AI achieve super-human performance in Atari games such as Breakout, Space Invaders, Seaquest and Beam Rider. Written in a clear and concise style, illustrated with animations and images, this book is particularly appealing to readers with no background in computer science, mathematics or statistics. Access the book's repository at:https://github.com/markhliu/MLA

Author : John David Funge
Publisher : CRC Press
Page : 160 pages
File Size : 41,5 Mb
Release : 2004-07-29
Category : Computers
ISBN : 9781439864807

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Artificial Intelligence for Computer Games by John David Funge Pdf

Learn to make games that are more fun and engaging! Building on fundamental principles of Artificial Intelligence, Funge explains how to create Non-Player Characters (NPCs) with progressively more sophisticated capabilities. Starting with the basic capability of acting in the game world, the book explains how to develop NPCs who can perceive, remem

Author : Micheal Lanham
Publisher : Packt Publishing Ltd
Page : 379 pages
File Size : 43,8 Mb
Release : 2019-03-30
Category : Computers
ISBN : 9781788998765

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Hands-On Deep Learning for Games by Micheal Lanham Pdf

Understand the core concepts of deep learning and deep reinforcement learning by applying them to develop games Key FeaturesApply the power of deep learning to complex reasoning tasks by building a Game AIExploit the most recent developments in machine learning and AI for building smart gamesImplement deep learning models and neural networks with PythonBook Description The number of applications of deep learning and neural networks has multiplied in the last couple of years. Neural nets has enabled significant breakthroughs in everything from computer vision, voice generation, voice recognition and self-driving cars. Game development is also a key area where these techniques are being applied. This book will give an in depth view of the potential of deep learning and neural networks in game development. We will take a look at the foundations of multi-layer perceptron’s to using convolutional and recurrent networks. In applications from GANs that create music or textures to self-driving cars and chatbots. Then we introduce deep reinforcement learning through the multi-armed bandit problem and other OpenAI Gym environments. As we progress through the book we will gain insights about DRL techniques such as Motivated Reinforcement Learning with Curiosity and Curriculum Learning. We also take a closer look at deep reinforcement learning and in particular the Unity ML-Agents toolkit. By the end of the book, we will look at how to apply DRL and the ML-Agents toolkit to enhance, test and automate your games or simulations. Finally, we will cover your possible next steps and possible areas for future learning. What you will learnLearn the foundations of neural networks and deep learning.Use advanced neural network architectures in applications to create music, textures, self driving cars and chatbots. Understand the basics of reinforcement and DRL and how to apply it to solve a variety of problems.Working with Unity ML-Agents toolkit and how to install, setup and run the kit.Understand core concepts of DRL and the differences between discrete and continuous action environments.Use several advanced forms of learning in various scenarios from developing agents to testing games.Who this book is for This books is for game developers who wish to create highly interactive games by leveraging the power of machine and deep learning. No prior knowledge of machine learning, deep learning or neural networks is required this book will teach those concepts from scratch. A good understanding of Python is required.

Author : Jun Yu,Dacheng Tao
Publisher : John Wiley & Sons
Page : 210 pages
File Size : 46,6 Mb
Release : 2013-03-27
Category : Computers
ISBN : 9781118559987

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Modern Machine Learning Techniques and Their Applications in Cartoon Animation Research by Jun Yu,Dacheng Tao Pdf

The integration of machine learning techniques and cartoon animation research is fast becoming a hot topic. This book helps readers learn the latest machine learning techniques, including patch alignment framework; spectral clustering, graph cuts, and convex relaxation; ensemble manifold learning; multiple kernel learning; multiview subspace learning; and multiview distance metric learning. It then presents the applications of these modern machine learning techniques in cartoon animation research. With these techniques, users can efficiently utilize the cartoon materials to generate animations in areas such as virtual reality, video games, animation films, and sport simulations

Author : Ian Millington
Publisher : CRC Press
Page : 92 pages
File Size : 45,7 Mb
Release : 2021-11-16
Category : Computers
ISBN : 9781000475562

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AI for Games by Ian Millington Pdf

What is artificial intelligence? How is artificial intelligence used in game development? Game development lives in its own technical world. It has its own idioms, skills, and challenges. That’s one of the reasons games are so much fun to work on. Each game has its own rules, its own aesthetic, and its own trade-offs, and the hardware it will run on keeps changing. AI for Games is designed to help you understand one element of game development: artificial intelligence (AI).

Author : Micheal Lanham
Publisher : Packt Publishing Ltd
Page : 420 pages
File Size : 45,8 Mb
Release : 2020-01-03
Category : Computers
ISBN : 9781839216770

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Hands-On Reinforcement Learning for Games by Micheal Lanham Pdf

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.

Author : Javid Taheri,Schahram Dustdar,Albert Zomaya,Shuiguang Deng
Publisher : Springer Nature
Page : 254 pages
File Size : 52,9 Mb
Release : 2023-06-14
Category : Computers
ISBN : 9783031221552

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Edge Intelligence by Javid Taheri,Schahram Dustdar,Albert Zomaya,Shuiguang Deng Pdf

This graduate-level textbook is ideally suited for lecturing the most relevant topics of Edge Computing and its ties to Artificial Intelligence (AI) and Machine Learning (ML) approaches. It starts from basics and gradually advances, step-by-step, to ways AI/ML concepts can help or benefit from Edge Computing platforms. The book is structured into seven chapters; each comes with its own dedicated set of teaching materials (practical skills, demonstration videos, questions, lab assignments, etc.). Chapter 1 opens the book and comprehensively introduces the concept of distributed computing continuum systems that led to the creation of Edge Computing. Chapter 2 motivates the use of container technologies and how they are used to implement programmable edge computing platforms. Chapter 3 introduces ways to employ AI/ML approaches to optimize service lifecycles at the edge. Chapter 4 goes deeper in the use of AI/ML and introduces ways to optimize spreading computational tasks along edge computing platforms. Chapter 5 introduces AI/ML pipelines to efficiently process generated data on the edge. Chapter 6 introduces ways to implement AI/ML systems on the edge and ways to deal with their training and inferencing procedures considering the limited resources available at the edge-nodes. Chapter 7 motivates the creation of a new orchestrator independent object model to descriptive objects (nodes, applications, etc.) and requirements (SLAs) for underlying edge platforms. To provide hands-on experience to students and step-by-step improve their technical capabilities, seven sets of Tutorials-and-Labs (TaLs) are also designed. Codes and Instructions for each TaL is provided on the book website, and accompanied by videos to facilitate their learning process.

Author : Diego Pérez Liébana,Simon M. Lucas,Raluca D. Gaina,Julian Togelius,Ahmed Khalifa,Jialin Liu
Publisher : Springer Nature
Page : 177 pages
File Size : 48,9 Mb
Release : 2022-05-31
Category : Mathematics
ISBN : 9783031021220

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General Video Game Artificial Intelligence by Diego Pérez Liébana,Simon M. Lucas,Raluca D. Gaina,Julian Togelius,Ahmed Khalifa,Jialin Liu Pdf

Research on general video game playing aims at designing agents or content generators that can perform well in multiple video games, possibly without knowing the game in advance and with little to no specific domain knowledge. The general video game AI framework and competition propose a challenge in which researchers can test their favorite AI methods with a potentially infinite number of games created using the Video Game Description Language. The open-source framework has been used since 2014 for running a challenge. Competitors around the globe submit their best approaches that aim to generalize well across games. Additionally, the framework has been used in AI modules by many higher-education institutions as assignments, or as proposed projects for final year (undergraduate and Master's) students and Ph.D. candidates. The present book, written by the developers and organizers of the framework, presents the most interesting highlights of the research performed by the authors during these years in this domain. It showcases work on methods to play the games, generators of content, and video game optimization. It also outlines potential further work in an area that offers multiple research directions for the future.

Author : Paul Roberts
Publisher : CRC Press
Page : 217 pages
File Size : 53,5 Mb
Release : 2024-02-23
Category : Computers
ISBN : 9781003847724

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Game AI Uncovered by Paul Roberts Pdf

Game AI Uncovered: Volume One kicks off a brand-new series of books that focus on the development of artificial intelligence in video games. This volume brings together the collected wisdom, ideas, tricks, and cutting-edge techniques from 20 of the top game AI professionals and researchers from around the world. The techniques discussed in these pages cover the underlying development of a wide array of published titles, including Hood: Outlaws and Legends, The Escapists 2, Sackboy: A Big Adventure, Call of Duty: Strike Team, GTI+ Club, Split/Second, Sonic All Stars Racing Transformed, Luna Abyss, Medal of Honor Heroes I & II, Age of Empires IV, Watch Dogs, Battlefield 2042, Plants vs. Zombies: Battle for Neighborville, Dead Space, and more. Contained within this volume are overviews and insight covering a host of different areas within game AI, including situational awareness, pathfinding, tethering, squad behaviours, coordination, auto-generating navigation link data, fluid movement, combining behaviour and animation systems, pedal control for cars, tactical positioning, level of detail, infinite axis utility systems, hierarchical state machines, bots for testing, reactive behaviour trees, and more. Beginners to the area of game AI, along with professional developers, will find a wealth of knowledge that will not only help in the development of your own games but will also spark ideas for new approaches. This volume includes chapters written by Andy Brown, Dr Allan Bruce, Richard Bull, Laurent Couvidou, Steven Dalton, Michele Ermacora, Jonas Gillberg, Dale Green, Johan Holthausen, Dr Aitor Santamaría Ibirika, Dr Nic Melder, Sarat Rallabandi, Bruno Rebaque, John Reynolds, Paul Roberts, David Rogers, Andrea Schiel, Huw Talliss, Dr Tommy Thompson, and David Wooldridge. .

Author : Niess, Margaret
Publisher : IGI Global
Page : 679 pages
File Size : 44,5 Mb
Release : 2016-04-22
Category : Education
ISBN : 9781522501213

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Handbook of Research on Transforming Mathematics Teacher Education in the Digital Age by Niess, Margaret Pdf

The digital age provides ample opportunities for enhanced learning experiences for students; however, it can also present challenges for educators who must adapt to and implement new technologies in the classroom. The Handbook of Research on Transforming Mathematics Teacher Education in the Digital Age is a critical reference source featuring the latest research on the development of educators’ knowledge for the integration of technologies to improve classroom instruction. Investigating emerging pedagogies for preservice and in-service teachers, this publication is ideal for professionals, researchers, and educational designers interested in the implementation of technology in the mathematics classroom.

Author : Tanmoy Hazra
Publisher : Springer Nature
Page : 93 pages
File Size : 48,8 Mb
Release : 2024-06-06
Category : Electronic
ISBN : 9783031546532

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Applications of Game Theory in Deep Learning by Tanmoy Hazra Pdf