Deep Reinforcement Learning and Its Industrial Use Cases: AI for Real-World Applications

ISBN 10: 1394272553 / ISBN 13: 9781394272556

Edité par Wiley-Scrivener, 2024

N° de réf. du vendeur 398248617

Synopsis :

"Deep Reinforcement Learning and its Industrial Use Cases: Harnessing AI for Real-World Applications" is an essential guide that supplies complex theories, practical insights, and diverse case studies behind deep reinforcement learning. This book offers a comprehensive look into how DLR is revolutionizing fields by implementing advanced algorithms in a variety of industries to solve real-world problems. Beyond the realm of successes of DLR, it critically examines challenges, pitfalls, and ethical considerations. This research and knowledge explore insights to meet the needs of curious enthusiasts eager to understand the cutting-edge technology shaping our future.

Throughout the pages of this book, we seek to discover the inner workings of DLR and its real-world applications. We start by laying down the foundational principles of reinforcement learning and building up to advanced DLR algorithms and techniques. Along the way, we delve into diverse case studies, examining how leading organizations harness the power of DLR to drive innovation and gain a competitive edge. From financial trading to autonomous manufacturing systems, each case study offers valuable insights into the practical considerations and challenges involved in deploying DLR solutions.

À propos de l?auteur:

Shubham Mahajan, PhD, is an assistant professor in the School of Engineering at Ajeekya D Y Patil University, Pune, Maharashtra, India. He has eight Indian, one Australian, and one German patent to his credit in artificial intelligence and image processing. He has authored/co-authored more than 50 publications including peer-reviewed journals and conferences. His main research interests include image processing, video compression, image segmentation, fuzzy entropy, and nature-inspired computing methods with applications in optimization, data mining, machine learning, robotics, and optical communication.

Pethuru Raj, PhD, is chief architect and vice president at Reliance Jio Platforms Ltd in Bangalore, India. He has a PhD in computer science and automation from the Indian Institute of Science in Bangalore, India. His areas of interest focus on artificial intelligence, model optimization, and reliability engineering. He has published thirty research papers and edited forty-two books.

Amit Kant Pandit, PhD, is an associate professor in the School of Electronics & Communication Engineering Shri Mata Vaishno Devi University, India. He has authored/co-authored more than 60 publications including peer-reviewed journals and conferences. He has two Indian and one Australian patent to his credit in artificial intelligence and image processing. His main research interests are image processing, video compression, image segmentation, fuzzy entropy, and nature-inspired computing methods with applications in optimization.

Détails bibliographiques

Titre : Deep Reinforcement Learning and Its ...
Éditeur : Wiley-Scrivener
Date d'édition : 2024
Reliure : Couverture rigide
Etat : New