Deep Learning in Gaming and Animations : Principles and Applications book cover
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Deep Learning in Gaming and Animations
Principles and Applications



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ISBN 9781032126098
December 16, 2021 Forthcoming by CRC Press
192 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 the reader through the fundamental ideas with expert ease. The book progresses on the topics 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, deep learning, and machine learning have changed the world in gaming and animation.

It gives us a motivation that AI can also be applied in gaming, and there are limited textbooks in this area. The book will comprehensively address all the aspects of AI & 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. Our book Deep Learning in Gaming and Animation teaches you how to apply the power of deep learning to build complex reasoning tasks. After exposing you to the foundations of the machine and deep learning, you will use Python to build a bot and then teach it the game's rules. We also focus on how different technologies have revolutionized gaming and animation with various illustrations.

Table of Contents

1. Checkers-AI: American Checkers Game Using Game Theory and Artificial Intelligence Algorithms
Priyanshi Gupta, Vividha, Preeti Nagrath*

2. The Future Of Automatically Generated Animation with AI
Preety Khatri*

3. Artificial Intelligence as Futuristic Approach for Narrative Gaming
Toka Haroun, Vikas Rao Naidu, Aparna Agarwal*

4. Review of using Artificial Intelligence related Deep Learning Techniques in Gaming and recent Networks

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

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

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

6. Artificial Intelligence in Games: Transforming the Gaming Skills
Abhisht Joshi*, Moolchand Sharma, Jafar Al Zubi

7. A Framework for Estimation of Generative Models through an Adversarial Process for Production of Animated Gaming Characters
Saad Bin Khalid,  Bramah Hazela*

8. Generative Adversarial Networks based PCG for games: A comprehensive study

Nimisha Mittal*, Priyanjali Pratap Singh, 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.