Deep Learning in Gaming and Animations : Principles and Applications book cover
1st Edition

Deep Learning in Gaming and Animations
Principles and Applications




ISBN 9781032126098
Published December 8, 2021 by CRC Press
174 Pages 67 B/W Illustrations

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Book Description

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.

Table of Contents

Chapter 1 Checkers-AI

Priyanshi Gupta , Vividha and Preeti Nagrath

Chapter 2 The Future of Automatically Generated Animation with AI

Preety Khatri

Chapter 3 Artificial Intelligence as Futuristic Approach for Narrative Gaming

Toka Haroun, Vikas Rao Naidu, and Aparna Agarwal

Chapter 4 Review on Using Artificial Intelligence Related Deep Learning Techniques in Gaming and Recent Networks

Mujahid Tabassum, Sundresan Perumal, Hadi Nabipour Afrouzi, Saad Bin Abdul Kashem, and Waqar Hassan

Chapter 5 A Review on Deep Learning Algorithms for Image Processing in Gaming and Animations

Sugandha Chakraverti, Ashish Kumar Chakraverti, Piyush Bhushan Singh, and Rakesh Ranjan

Chapter 6 Artificial Intelligence in Games

Abhisht Joshi, Moolchand Sharma, and Jafar Al Zubi

Chapter 7 A Framework for Estimation of Generative Models Through an Adversarial Process for Production of Animated Gaming Characters

Saad Bin Khalid and Bramah Hazela

Chapter 8 Generative Adversarial Networks Based PCG for Games

Nimisha Mittal, Priyanjali Pratap Singh, and Prerna Sharma

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Editor(s)

Biography

Vikas Chaudhary is working as a professor in the Computer Science & Engineering department at JIMS Engineering Management Technical Campus, Greater Noida. He has 18 years of teaching and research experience. He has obtained a Doctorate from the National Institute of Technology, Kurukshetra, India, in Machine Learning/ Unsupervised Learning. He has published various research papers in the International Journals of Springer, Elsevier, Taylor & Francis. Also, he has published various papers in IEEE International Conferences and national conferences. He is a reviewer of Springer Journal as well as of many IEEE conferences. He has written a book on Cryptography & Network Security. His research area is Machine Learning, Artificial Neural Networks.

Moolchand Sharma is currently an Assistant Professor in the Department of Computer Science and Engineering at Maharaja Agrasen Institute of Technology, GGSIPU Delhi. He has published scientific research publications in reputed International Journals and Conferences, including SCI indexed and Scopus indexed Journals such as Cognitive Systems Research (Elsevier), Physical Communication(Elsevier), Intelligent Decision Technologies: An International Journal, Cyber-Physical Systems (Taylor & Francis Group), International Journal of Image & Graphics (World Scientific), International Journal of Innovative Computing and Applications (Inderscience) & Innovative Computing and Communication Journal (Scientific Peer-reviewed Journal). He has authored/co-authored in chapters with International publishers like Elsevier, Wiley, De Gruyter. He has authored/ edited three books with a National/International level publisher (CRC Press, Bhavya publications). His research area includes Artificial Intelligence, Nature-Inspired Computing, Security in Cloud Computing, Machine Learning, and Search Engine Optimization. He is associated with various professional bodies like ISTE, IAENG, ICSES, UACEE, Internet Society, etc. He possesses teaching experience of more than nine years. He is the co-convener of the ICICC-2018, ICICC-2019& ICICC-2020 springer conference series and also the co-convener of ICCRDA-2020 Scopus Indexed IOP Material Science &Engineering conference series. He is also the reviewer of many reputed journals like Springer, Elsevier, IEEE, Wiley, Taylor & Francis Group and World Scientific Journal, and many springer conferences. He is currently a doctoral researcher at DCR University of Science & Technology, Haryana. He completed his Post Graduate in 2012 from SRM UNIVERSITY, NCR CAMPUS, GHAZIABAD, and Graduate in 2010 from KNGD MODI ENGG. COLLEGE, GBTU.

Prerna Sharma is currently an Assistant Professor in the Department of Computer Science and Engineering at Maharaja Agrasen Institute of Technology, GGSIPU Delhi. She has authored/co-authored SCI-indexed journal and Scopus indexed journal articles in high ranked and prestigious journals such as Journal of Supercomputing(Springer), Cognitive Systems Research(Elsevier), Expert Systems (Wiley) International Journal of Innovative Computing and Applications (Inderscience). She has also authored book chapters with International level publishers (Wiley & Elsevier). She has extensively worked on Computational Intelligence. Her area of interest includes Artificial Intelligence, Machine learning, Nature-Inspired Computing, Soft Computing, and Cloud computing. She is associated with various professional bodies like IAENG, ICSES, UACEE, Internet Society, etc. She has a rich academic background and teaching experience of 8 years. She is a doctoral researcher at Delhi Technological University (DTU), Delhi. She completed her Post Graduate in 2011 from USIT, GGSIPU, and Graduate in 2009 from GPMCE, GGSIPU.

Deevyankar Agarwal is working as a lecturer in the Engineering Department–EEE Section (Computer Engineering) at the University of Technology & Applied Sciences(Public University), Muscat, Oman. He has 20 years of teaching and research experience. He is currently a doctoral researcher at the University of Valladolid, Spain. He has published various research papers in the International Journals of Springer, Elsevier, Taylor & Francis. Also, he has published various papers in IEEE International Conferences and national conferences. He is a reviewer of Springer Journal as well as of many IEEE conferences.