Deep Reinforcement Learning And Its Industrial Use Cases
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Deep Reinforcement Learning And Its Industrial Use Cases
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Author : Shubham Mahajan
language : en
Publisher: John Wiley & Sons
Release Date : 2024-10-01
Deep Reinforcement Learning And Its Industrial Use Cases written by Shubham Mahajan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-01 with Computers categories.
This book serves as a bridge connecting the theoretical foundations of DRL with practical, actionable insights for implementing these technologies in a variety of industrial contexts, making it a valuable resource for professionals and enthusiasts at the forefront of technological innovation. Deep Reinforcement Learning (DRL) represents one of the most dynamic and impactful areas of research and development in the field of artificial intelligence. Bridging the gap between decision-making theory and powerful deep learning models, DRL has evolved from academic curiosity to a cornerstone technology driving innovation across numerous industries. Its core premise—enabling machines to learn optimal actions within complex environments through trial and error—has broad implications, from automating intricate decision processes to optimizing operations that were previously beyond the reach of traditional AI techniques. “Deep Reinforcement Learning and Its Industrial Use Cases: AI for Real-World Applications” is an essential guide for anyone eager to understand the nexus between cutting-edge artificial intelligence techniques and practical industrial applications. This book not only demystifies the complex theory behind deep reinforcement learning (DRL) but also provides a clear roadmap for implementing these advanced algorithms in a variety of industries to solve real-world problems. Through a careful blend of theoretical foundations, practical insights, and diverse case studies, the book offers a comprehensive look into how DRL is revolutionizing fields such as finance, healthcare, manufacturing, and more, by optimizing decisions in dynamic and uncertain environments. This book distills years of research and practical experience into accessible and actionable knowledge. Whether you’re an AI professional seeking to expand your toolkit, a business leader aiming to leverage AI for competitive advantage, or a student or academic researching the latest in AI applications, this book provides valuable insights and guidance. Beyond just exploring the successes of DRL, it critically examines challenges, pitfalls, and ethical considerations, preparing readers to not only implement DRL solutions but to do so responsibly and effectively. Audience The book will be read by researchers, postgraduate students, and industry engineers in machine learning and artificial intelligence, as well as those in business and industry seeking to understand how DRL can be applied to solve complex industry-specific challenges and improve operational efficiency.
Deep Reinforcement Learning And Its Industrial Use Cases
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Author : Shubham Mahajan
language : en
Publisher: John Wiley & Sons
Release Date : 2024-10-29
Deep Reinforcement Learning And Its Industrial Use Cases written by Shubham Mahajan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-29 with Computers categories.
This book serves as a bridge connecting the theoretical foundations of DRL with practical, actionable insights for implementing these technologies in a variety of industrial contexts, making it a valuable resource for professionals and enthusiasts at the forefront of technological innovation. Deep Reinforcement Learning (DRL) represents one of the most dynamic and impactful areas of research and development in the field of artificial intelligence. Bridging the gap between decision-making theory and powerful deep learning models, DRL has evolved from academic curiosity to a cornerstone technology driving innovation across numerous industries. Its core premise—enabling machines to learn optimal actions within complex environments through trial and error—has broad implications, from automating intricate decision processes to optimizing operations that were previously beyond the reach of traditional AI techniques. “Deep Reinforcement Learning and Its Industrial Use Cases: AI for Real-World Applications” is an essential guide for anyone eager to understand the nexus between cutting-edge artificial intelligence techniques and practical industrial applications. This book not only demystifies the complex theory behind deep reinforcement learning (DRL) but also provides a clear roadmap for implementing these advanced algorithms in a variety of industries to solve real-world problems. Through a careful blend of theoretical foundations, practical insights, and diverse case studies, the book offers a comprehensive look into how DRL is revolutionizing fields such as finance, healthcare, manufacturing, and more, by optimizing decisions in dynamic and uncertain environments. This book distills years of research and practical experience into accessible and actionable knowledge. Whether you’re an AI professional seeking to expand your toolkit, a business leader aiming to leverage AI for competitive advantage, or a student or academic researching the latest in AI applications, this book provides valuable insights and guidance. Beyond just exploring the successes of DRL, it critically examines challenges, pitfalls, and ethical considerations, preparing readers to not only implement DRL solutions but to do so responsibly and effectively. Audience The book will be read by researchers, postgraduate students, and industry engineers in machine learning and artificial intelligence, as well as those in business and industry seeking to understand how DRL can be applied to solve complex industry-specific challenges and improve operational efficiency.
Reinforcement Learning
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Author : Phil Winder Ph.D.
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2020-11-06
Reinforcement Learning written by Phil Winder Ph.D. and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-06 with Computers categories.
Reinforcement learning (RL) will deliver one of the biggest breakthroughs in AI over the next decade, enabling algorithms to learn from their environment to achieve arbitrary goals. This exciting development avoids constraints found in traditional machine learning (ML) algorithms. This practical book shows data science and AI professionals how to learn by reinforcement and enable a machine to learn by itself. Author Phil Winder of Winder Research covers everything from basic building blocks to state-of-the-art practices. You'll explore the current state of RL, focus on industrial applications, learn numerous algorithms, and benefit from dedicated chapters on deploying RL solutions to production. This is no cookbook; doesn't shy away from math and expects familiarity with ML. Learn what RL is and how the algorithms help solve problems Become grounded in RL fundamentals including Markov decision processes, dynamic programming, and temporal difference learning Dive deep into a range of value and policy gradient methods Apply advanced RL solutions such as meta learning, hierarchical learning, multi-agent, and imitation learning Understand cutting-edge deep RL algorithms including Rainbow, PPO, TD3, SAC, and more Get practical examples through the accompanying website
Deep Reinforcement Learning
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Author : Mohit Sewak
language : en
Publisher: Springer
Release Date : 2019-06-27
Deep Reinforcement Learning written by Mohit Sewak and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-27 with Computers categories.
This book starts by presenting the basics of reinforcement learning using highly intuitive and easy-to-understand examples and applications, and then introduces the cutting-edge research advances that make reinforcement learning capable of out-performing most state-of-art systems, and even humans in a number of applications. The book not only equips readers with an understanding of multiple advanced and innovative algorithms, but also prepares them to implement systems such as those created by Google Deep Mind in actual code. This book is intended for readers who want to both understand and apply advanced concepts in a field that combines the best of two worlds – deep learning and reinforcement learning – to tap the potential of ‘advanced artificial intelligence’ for creating real-world applications and game-winning algorithms.
Smart Computing Techniques In Industrial Iot
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Author : Chiranji Lal Chowdhary
language : en
Publisher: Springer Nature
Release Date : 2024-10-19
Smart Computing Techniques In Industrial Iot written by Chiranji Lal Chowdhary and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-19 with Computers categories.
The book provides a conceptual framework and roadmap for applications and research trends in Smart Computing Techniques in Industrial IoT. This volume aims to provide information on emerging fields of intelligent computing techniques with a particular emphasis on industrial IoT development and applications of artificial intelligence, deep learning techniques, computational intelligence methods, the Internet of Medical Things (IoMT), optimization techniques, blockchain, and cloud computing. It will be a useful guide for undergraduate and postgraduate students studying artificial intelligence, deep learning, industry 4.0, industry 5.0, smart cities, machine learning, deep learning computational intelligence, and edge/cloud computing.
Machine Learning For Beginners
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Author : Manish Soni
language : en
Publisher:
Release Date : 2024-12-01
Machine Learning For Beginners written by Manish Soni and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-01 with Study Aids categories.
This book is designed to be more than just a traditional textbook; it is a complete learning resource tailored to meet the needs of learners at all levels. Whether you are a student embarking on your first journey into deep learning or an experienced professional seeking to deepen your knowledge and skills, this guide provides the tools and resources necessary to achieve your goals.
Service Oriented Holonic And Multi Agent Manufacturing Systems For Industry Of The Future
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Author : Theodor Borangiu
language : en
Publisher: Springer Nature
Release Date : 2023-02-01
Service Oriented Holonic And Multi Agent Manufacturing Systems For Industry Of The Future written by Theodor Borangiu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-01 with Technology & Engineering categories.
The scientific theme of the book is “Virtualisation – a multifaceted key enabler of Industry 4.0 from holonic to cloud manufacturing” which is addressed in the framework of cyber-physical system development. The book approaches cyber-physical systems for manufacturing with emergent digital technologies: Internet of Things, digital twins (based on the virtualization of production models embedded in the design, virtual commissioning, optimization and resilience of processes and fault tolerance of resources), big data, cloud control and computing, machine learning and cobots, that are applied in the book’s chapters to industry and service sectors such as manufacturing, energy, logistics, construction and health care. The novelty of this approach consists in interpreting and applying the characteristics of RAMI4.0—the reference architecture model of the Industry 4.0 framework—as combinations of virtualized cyber-physical system elements and IT components in life cycle value stream models. The general scope of the book is to foster innovation in smart and sustainable manufacturing and logistics systems and in this context to promote concepts, methods and solutions for the digital transformation of manufacturing through service orientation in holonic and agent-based control with distributed intelligence. The book’s readership is comprised by researchers and engineers working in the manufacturing value chain area who develop and use digital control solutions in the “Industry of the Future” vision. The book also addresses to master’s and Ph.D. students enrolled in Engineering Sciences programs.
Blockchain For 5g Enabled Iot
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Author : Sudeep Tanwar
language : en
Publisher: Springer Nature
Release Date : 2021-04-09
Blockchain For 5g Enabled Iot written by Sudeep Tanwar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-09 with Technology & Engineering categories.
This book addresses one of the most overlooked practical, methodological, and moral questions in the journey to secure and handle the massive amount of data being generated from smart devices interactions: the integration of Blockchain with 5G-enabled IoT. After an overview, this book discusses open issues and challenges, which may hinder the growth of Blockchain technology. Then, this book presents a variety of perspectives on the most pressing questions in the field, such as: how IoT can connect billions of objects together; how the access control mechanisms in 5G-enabled industrial environment works; how to address the real-time and quality-of-service requirements for industrial applications; and how to ensure scalability and computing efficiency. Also, it includes a detailed discussions on the complexity of adoption of Blockchain for 5G-Enabled IoT and presents comparative case studies with respect to various performance evaluation metrics such as scalability, data management, standardization, interoperability and regulations, accessibility, human-factors engineering and interfaces, reliability, heterogeneity, and QoS requirements. This book acts as a professional guide for the practitioners in information security and related topics.
Artificial Intelligence In Healthcare Industry
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Author : Jyotismita Talukdar
language : en
Publisher: Springer Nature
Release Date : 2023-07-01
Artificial Intelligence In Healthcare Industry written by Jyotismita Talukdar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-01 with Computers categories.
This book presents a systematic evolution of artificial intelligence (AI), its applications, challenges and solutions in the field of healthcare. The book mainly covers the foundations and various methods of learning in artificial intelligence with its application in healthcare industry. This book provides a comprehensive introduction to data analysis using AI as a tool in the generation, normalization and analysis of healthcare data in association with several evaluation techniques and accuracy measurements. The book is divided into three major sections describing the basic foundations of AI and its associated algorithms, history of artificial intelligence in healthcare, recent developments and several modeling techniques for the same. The last section of the book provides insights into several implementations and methods of evaluation and accuracy prediction for healthcare analysis in AI. Extensive use of data for analysis and prediction using several technologies has transformed the lives of normal people indirectly effecting our process to communicate, learn, work and socialize within the society. Thus, the book also provides an insight into the ethics of AI that is very vital in the process of implementation and evaluation of healthcare data. The book provides an organized analysis to a considerable part of data in a digitized society. In view of this, it covers the theory, methodology, perfection and verification of empirical work for health-related data processing. Particular attention is devoted to in-depth experiments and applications.
Towards Sustainable Customization Bridging Smart Products And Manufacturing Systems
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Author : Ann-Louise Andersen
language : en
Publisher: Springer Nature
Release Date : 2021-10-31
Towards Sustainable Customization Bridging Smart Products And Manufacturing Systems written by Ann-Louise Andersen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-31 with Technology & Engineering categories.
This book features state-of-the-art contributions from two well-established conferences: Changeable, Agile, Reconfigurable and Virtual Production Conference (CARV2020) and Mass Customization and Personalization Conference (MCPC2020). Together, they focus on the joint design, development, and management of products, production systems, and business for sustainable customization and personalization. The book covers a large range of topics within this domain, ranging from industrial success factors to original contributions within the field.