Federated Learning For Future Intelligent Wireless Networks

Download Federated Learning For Future Intelligent Wireless Networks full books in PDF, epub, and Kindle. Read online Federated Learning For Future Intelligent Wireless Networks ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Federated Learning for Future Intelligent Wireless Networks

Author : Yao Sun
Publisher : John Wiley & Sons
ISBN 13 : 1119913918
Total Pages : 324 pages
Book Rating : 4.1/5 (199 download)

DOWNLOAD NOW!

Book Synopsis Federated Learning for Future Intelligent Wireless Networks by : Yao Sun

Download or read book Federated Learning for Future Intelligent Wireless Networks written by Yao Sun and published by John Wiley & Sons. This book was released on 2023-12-04 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Federated Learning for Future Intelligent Wireless Networks Explore the concepts, algorithms, and applications underlying federated learning In Federated Learning for Future Intelligent Wireless Networks, a team of distinguished researchers deliver a robust and insightful collection of resources covering the foundational concepts and algorithms powering federated learning, as well as explanations of how they can be used in wireless communication systems. The editors have included works that examine how communication resource provision affects federated learning performance, accuracy, convergence, scalability, and security and privacy. Readers will explore a wide range of topics that show how federated learning algorithms, concepts, and design and optimization issues apply to wireless communications. Readers will also find: A thorough introduction to the fundamental concepts and algorithms of federated learning, including horizontal, vertical, and hybrid FL Comprehensive explorations of wireless communication network design and optimization for federated learning Practical discussions of novel federated learning algorithms and frameworks for future wireless networks Expansive case studies in edge intelligence, autonomous driving, IoT, MEC, blockchain, and content caching and distribution Perfect for electrical and computer science engineers, researchers, professors, and postgraduate students with an interest in machine learning, Federated Learning for Future Intelligent Wireless Networks will also benefit regulators and institutional actors responsible for overseeing and making policy in the area of artificial intelligence.

Federated Learning for Future Intelligent Wireless Networks

Author : Yao Sun
Publisher : John Wiley & Sons
ISBN 13 : 1119913896
Total Pages : 324 pages
Book Rating : 4.1/5 (199 download)

DOWNLOAD NOW!

Book Synopsis Federated Learning for Future Intelligent Wireless Networks by : Yao Sun

Download or read book Federated Learning for Future Intelligent Wireless Networks written by Yao Sun and published by John Wiley & Sons. This book was released on 2023-12-27 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Federated Learning for Future Intelligent Wireless Networks Explore the concepts, algorithms, and applications underlying federated learning In Federated Learning for Future Intelligent Wireless Networks, a team of distinguished researchers deliver a robust and insightful collection of resources covering the foundational concepts and algorithms powering federated learning, as well as explanations of how they can be used in wireless communication systems. The editors have included works that examine how communication resource provision affects federated learning performance, accuracy, convergence, scalability, and security and privacy. Readers will explore a wide range of topics that show how federated learning algorithms, concepts, and design and optimization issues apply to wireless communications. Readers will also find: A thorough introduction to the fundamental concepts and algorithms of federated learning, including horizontal, vertical, and hybrid FL Comprehensive explorations of wireless communication network design and optimization for federated learning Practical discussions of novel federated learning algorithms and frameworks for future wireless networks Expansive case studies in edge intelligence, autonomous driving, IoT, MEC, blockchain, and content caching and distribution Perfect for electrical and computer science engineers, researchers, professors, and postgraduate students with an interest in machine learning, Federated Learning for Future Intelligent Wireless Networks will also benefit regulators and institutional actors responsible for overseeing and making policy in the area of artificial intelligence.

Communication Efficient Federated Learning for Wireless Networks

Author : Mingzhe Chen
Publisher : Springer Nature
ISBN 13 : 3031512669
Total Pages : 189 pages
Book Rating : 4.0/5 (315 download)

DOWNLOAD NOW!

Book Synopsis Communication Efficient Federated Learning for Wireless Networks by : Mingzhe Chen

Download or read book Communication Efficient Federated Learning for Wireless Networks written by Mingzhe Chen and published by Springer Nature. This book was released on with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Machine Learning for Future Wireless Communications

Author : Fa-Long Luo
Publisher : John Wiley & Sons
ISBN 13 : 1119562252
Total Pages : 490 pages
Book Rating : 4.1/5 (195 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning for Future Wireless Communications by : Fa-Long Luo

Download or read book Machine Learning for Future Wireless Communications written by Fa-Long Luo and published by John Wiley & Sons. This book was released on 2020-02-10 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author – a noted expert on the topic – covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource: Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks Covers a range of topics from architecture and optimization to adaptive resource allocations Reviews state-of-the-art machine learning based solutions for network coverage Includes an overview of the applications of machine learning algorithms in future wireless networks Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.

Federated Learning for Wireless Networks

Author : Choong Seon Hong
Publisher : Springer Nature
ISBN 13 : 9811649634
Total Pages : 257 pages
Book Rating : 4.8/5 (116 download)

DOWNLOAD NOW!

Book Synopsis Federated Learning for Wireless Networks by : Choong Seon Hong

Download or read book Federated Learning for Wireless Networks written by Choong Seon Hong and published by Springer Nature. This book was released on 2022-01-01 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently machine learning schemes have attained significant attention as key enablers for next-generation wireless systems. Currently, wireless systems are mostly using machine learning schemes that are based on centralizing the training and inference processes by migrating the end-devices data to a third party centralized location. However, these schemes lead to end-devices privacy leakage. To address these issues, one can use a distributed machine learning at network edge. In this context, federated learning (FL) is one of most important distributed learning algorithm, allowing devices to train a shared machine learning model while keeping data locally. However, applying FL in wireless networks and optimizing the performance involves a range of research topics. For example, in FL, training machine learning models require communication between wireless devices and edge servers via wireless links. Therefore, wireless impairments such as uncertainties among wireless channel states, interference, and noise significantly affect the performance of FL. On the other hand, federated-reinforcement learning leverages distributed computation power and data to solve complex optimization problems that arise in various use cases, such as interference alignment, resource management, clustering, and network control. Traditionally, FL makes the assumption that edge devices will unconditionally participate in the tasks when invited, which is not practical in reality due to the cost of model training. As such, building incentive mechanisms is indispensable for FL networks. This book provides a comprehensive overview of FL for wireless networks. It is divided into three main parts: The first part briefly discusses the fundamentals of FL for wireless networks, while the second part comprehensively examines the design and analysis of wireless FL, covering resource optimization, incentive mechanism, security and privacy. It also presents several solutions based on optimization theory, graph theory, and game theory to optimize the performance of federated learning in wireless networks. Lastly, the third part describes several applications of FL in wireless networks.

Federated Learning Over Wireless Edge Networks

Author : Wei Yang Bryan Lim
Publisher : Springer Nature
ISBN 13 : 3031078381
Total Pages : 175 pages
Book Rating : 4.0/5 (31 download)

DOWNLOAD NOW!

Book Synopsis Federated Learning Over Wireless Edge Networks by : Wei Yang Bryan Lim

Download or read book Federated Learning Over Wireless Edge Networks written by Wei Yang Bryan Lim and published by Springer Nature. This book was released on 2022-09-28 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book first presents a tutorial on Federated Learning (FL) and its role in enabling Edge Intelligence over wireless edge networks. This provides readers with a concise introduction to the challenges and state-of-the-art approaches towards implementing FL over the wireless edge network. Then, in consideration of resource heterogeneity at the network edge, the authors provide multifaceted solutions at the intersection of network economics, game theory, and machine learning towards improving the efficiency of resource allocation for FL over the wireless edge networks. A clear understanding of such issues and the presented theoretical studies will serve to guide practitioners and researchers in implementing resource-efficient FL systems and solving the open issues in FL respectively.

Data-Driven Intelligence in Wireless Networks

Author : Muhammad Khalil Afzal
Publisher : CRC Press
ISBN 13 : 1000841332
Total Pages : 267 pages
Book Rating : 4.0/5 (8 download)

DOWNLOAD NOW!

Book Synopsis Data-Driven Intelligence in Wireless Networks by : Muhammad Khalil Afzal

Download or read book Data-Driven Intelligence in Wireless Networks written by Muhammad Khalil Afzal and published by CRC Press. This book was released on 2023-03-27 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covers details on wireless communication problems, conducive for data-driven solutions Provides a comprehensive account of programming languages, tools, techniques, and good practices Provides an introduction to data-driven techniques applied to wireless communication systems Examines data-driven techniques, performance, and design issues in wireless networks Includes several case studies that examine data-driven solution for QoS in heterogeneous wireless networks

Future Wireless Networks and Information Systems

Author : Ying Zhang
Publisher : Springer Science & Business Media
ISBN 13 : 3642273238
Total Pages : 762 pages
Book Rating : 4.6/5 (422 download)

DOWNLOAD NOW!

Book Synopsis Future Wireless Networks and Information Systems by : Ying Zhang

Download or read book Future Wireless Networks and Information Systems written by Ying Zhang and published by Springer Science & Business Media. This book was released on 2012-02-01 with total page 762 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains revised and extended research articles written by prominent researchers participating in ICFWI 2011 conference. The 2011 International Conference on Future Wireless Networks and Information Systems (ICFWI 2011) has been held on November 30 ~ December 1, 2011, Macao, China. Topics covered include Wireless Information Networks, Wireless Networking Technologies, Mobile Software and Services, intelligent computing, network management, power engineering, control engineering, Signal and Image Processing, Machine Learning, Control Systems and Applications, The book will offer the states of arts of tremendous advances in Wireless Networks and Information Systems and also serve as an excellent reference work for researchers and graduate students working on Wireless Networks and Information Systems.

Future Wireless Networks and Information Systems

Author : Ying Zhang
Publisher : Springer Science & Business Media
ISBN 13 : 3642273262
Total Pages : 764 pages
Book Rating : 4.6/5 (422 download)

DOWNLOAD NOW!

Book Synopsis Future Wireless Networks and Information Systems by : Ying Zhang

Download or read book Future Wireless Networks and Information Systems written by Ying Zhang and published by Springer Science & Business Media. This book was released on 2012-01-25 with total page 764 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains revised and extended research articles written by prominent researchers participating in the ICF4C 2011 conference. 2011 International Conference on Future Communication, Computing, Control and Management (ICF4C 2011) has been held on December 16-17, 2011, Phuket, Thailand. Topics covered include intelligent computing, network management, wireless networks, telecommunication, power engineering, control engineering, Signal and Image Processing, Machine Learning, Control Systems and Applications, The book will offer the states of arts of tremendous advances in Computing, Communication, Control, and Management and also serve as an excellent reference work for researchers and graduate students working on Computing, Communication, Control, and Management Research.

Towards User-Centric Intelligent Network Selection in 5G Heterogeneous Wireless Networks

Author : Zhiyong Du
Publisher : Springer Nature
ISBN 13 : 9811511209
Total Pages : 136 pages
Book Rating : 4.8/5 (115 download)

DOWNLOAD NOW!

Book Synopsis Towards User-Centric Intelligent Network Selection in 5G Heterogeneous Wireless Networks by : Zhiyong Du

Download or read book Towards User-Centric Intelligent Network Selection in 5G Heterogeneous Wireless Networks written by Zhiyong Du and published by Springer Nature. This book was released on 2019-11-06 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents reinforcement learning (RL) based solutions for user-centric online network selection optimization. The main content can be divided into three parts. The first part (chapter 2 and 3) focuses on how to learning the best network when QoE is revealed beyond QoS under the framework of multi-armed bandit (MAB). The second part (chapter 4 and 5) focuses on how to meet dynamic user demand in complex and uncertain heterogeneous wireless networks under the framework of markov decision process (MDP). The third part (chapter 6 and 7) focuses on how to meet heterogeneous user demand for multiple users inlarge-scale networks under the framework of game theory. Efficient RL algorithms with practical constraints and considerations are proposed to optimize QoE for realizing intelligent online network selection for future mobile networks. This book is intended as a reference resource for researchers and designers in resource management of 5G networks and beyond.

Machine Learning and Wireless Communications

Author : Yonina C. Eldar
Publisher : Cambridge University Press
ISBN 13 : 1108967736
Total Pages : 560 pages
Book Rating : 4.1/5 (89 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning and Wireless Communications by : Yonina C. Eldar

Download or read book Machine Learning and Wireless Communications written by Yonina C. Eldar and published by Cambridge University Press. This book was released on 2022-06-30 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can machine learning help the design of future communication networks – and how can future networks meet the demands of emerging machine learning applications? Discover the interactions between two of the most transformative and impactful technologies of our age in this comprehensive book. First, learn how modern machine learning techniques, such as deep neural networks, can transform how we design and optimize future communication networks. Accessible introductions to concepts and tools are accompanied by numerous real-world examples, showing you how these techniques can be used to tackle longstanding problems. Next, explore the design of wireless networks as platforms for machine learning applications – an overview of modern machine learning techniques and communication protocols will help you to understand the challenges, while new methods and design approaches will be presented to handle wireless channel impairments such as noise and interference, to meet the demands of emerging machine learning applications at the wireless edge.

Next-Generation Wireless Networks Meet Advanced Machine Learning Applications

Author : Com?a, Ioan-Sorin
Publisher : IGI Global
ISBN 13 : 152257459X
Total Pages : 356 pages
Book Rating : 4.5/5 (225 download)

DOWNLOAD NOW!

Book Synopsis Next-Generation Wireless Networks Meet Advanced Machine Learning Applications by : Com?a, Ioan-Sorin

Download or read book Next-Generation Wireless Networks Meet Advanced Machine Learning Applications written by Com?a, Ioan-Sorin and published by IGI Global. This book was released on 2019-01-25 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ever-evolving wireless technology industry is demanding new technologies and standards to ensure a higher quality of experience for global end-users. This developing challenge has enabled researchers to identify the present trend of machine learning as a possible solution, but will it meet business velocity demand? Next-Generation Wireless Networks Meet Advanced Machine Learning Applications is a pivotal reference source that provides emerging trends and insights into various technologies of next-generation wireless networks to enable the dynamic optimization of system configuration and applications within the fields of wireless networks, broadband networks, and wireless communication. Featuring coverage on a broad range of topics such as machine learning, hybrid network environments, wireless communications, and the internet of things; this publication is ideally designed for industry experts, researchers, students, academicians, and practitioners seeking current research on various technologies of next-generation wireless networks.

Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems

Author : K. Suganthi
Publisher : CRC Press
ISBN 13 : 1000441814
Total Pages : 296 pages
Book Rating : 4.0/5 (4 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems by : K. Suganthi

Download or read book Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems written by K. Suganthi and published by CRC Press. This book was released on 2021-09-14 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers the latest advances and results in the fields of Machine Learning and Deep Learning for Wireless Communication and provides positive and critical discussions on the challenges and prospects. It provides a broad spectrum in understanding the improvements in Machine Learning and Deep Learning that are motivating by the specific constraints posed by wireless networking systems. The book offers an extensive overview on intelligent Wireless Communication systems and its underlying technologies, research challenges, solutions, and case studies. It provides information on intelligent wireless communication systems and its models, algorithms and applications. The book is written as a reference that offers the latest technologies and research results to various industry problems.

Machine Learning for Future Wireless Communications

Author : Fa-Long Luo
Publisher : Wiley-IEEE Press
ISBN 13 : 9781119562306
Total Pages : 496 pages
Book Rating : 4.5/5 (623 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning for Future Wireless Communications by : Fa-Long Luo

Download or read book Machine Learning for Future Wireless Communications written by Fa-Long Luo and published by Wiley-IEEE Press. This book was released on 2019-12-13 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author - a noted expert on the topic - covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource: Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks Covers a range of topics from architecture and optimization to adaptive resource allocations Reviews state-of-the-art machine learning based solutions for network coverage Includes an overview of the applications of machine learning algorithms in future wireless networks Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.

Green Machine Learning Protocols for Future Communication Networks

Author : Saim Ghafoor
Publisher : CRC Press
ISBN 13 : 1000968928
Total Pages : 223 pages
Book Rating : 4.0/5 (9 download)

DOWNLOAD NOW!

Book Synopsis Green Machine Learning Protocols for Future Communication Networks by : Saim Ghafoor

Download or read book Green Machine Learning Protocols for Future Communication Networks written by Saim Ghafoor and published by CRC Press. This book was released on 2023-10-25 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning has shown tremendous benefits in solving complex network problems and providing situation and parameter prediction. However, heavy resources are required to process and analyze the data, which can be done either offline or using edge computing but also requires heavy transmission resources to provide a timely response. The need here is to provide lightweight machine learning protocols that can process and analyze the data at run time and provide a timely and efficient response. These algorithms have grown in terms of computation and memory requirements due to the availability of large data sets. These models/algorithms also require high levels of resources such as computing, memory, communication, and storage. The focus so far was on producing highly accurate models for these communication networks without considering the energy consumption of these machine learning algorithms. For future scalable and sustainable network applications, efforts are required toward designing new machine learning protocols and modifying the existing ones, which consume less energy, i.e., green machine learning protocols. In other words, novel and lightweight green machine learning algorithms/protocols are required to reduce energy consumption which can also reduce the carbon footprint. To realize the green machine learning protocols, this book presents different aspects of green machine learning for future communication networks. This book highlights mainly the green machine learning protocols for cellular communication, federated learning-based models, and protocols for Beyond Fifth Generation networks, approaches for cloud-based communications, and Internet-of-Things. This book also highlights the design considerations and challenges for green machine learning protocols for different future applications.

Intelligent Wireless Sensor Networks and the Internet of Things

Author : Bhanu Chander
Publisher : CRC Press
ISBN 13 : 1040027121
Total Pages : 368 pages
Book Rating : 4.0/5 (4 download)

DOWNLOAD NOW!

Book Synopsis Intelligent Wireless Sensor Networks and the Internet of Things by : Bhanu Chander

Download or read book Intelligent Wireless Sensor Networks and the Internet of Things written by Bhanu Chander and published by CRC Press. This book was released on 2024-06-12 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: The edited book Intelligent Wireless Sensor Networks and Internet of Things: Algorithms, Methodologies and Applications is intended to discuss the progression of recent as well as future generation technologies for WSNs and IoTs applications through Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL). In general, computing time is obviously increased when the massive data is required from sensor nodes in WSN’s. the novel technologies such as 5G and 6G provides enough bandwidth for large data transmissions, however, unbalanced links faces the novel constraints on the geographical topology of the sensor networks. Above and beyond, data transmission congestion and data queue still happen in the WSNs. This book: Addresses the complete functional framework workflow in WSN and IoT domains using AI, ML, and DL models Explores basic and high-level concepts of WSN security, and routing protocols, thus serving as a manual for those in the research field as the beginners to understand both basic and advanced aspects sensors, IoT with ML & DL applications in real-world related technology Based on the latest technologies such as 5G, 6G and covering the major challenges, issues, and advances of protocols, and applications in wireless system Explores intelligent route discovering, identification of research problems and its implications to the real world Explains concepts of IoT communication protocols, intelligent sensors, statistics and exploratory data analytics, computational intelligence, machine learning, and Deep learning algorithms for betterment of the smarter humanity Explores intelligent data processing, deep learning frameworks, and multi-agent systems in IoT-enabled WSN system This book demonstrates and discovers the objectives, goals, challenges, and related solutions in advanced AI, ML, and DL approaches This book is for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

Deep Reinforcement Learning for Wireless Networks

Author : F. Richard Yu
Publisher : Springer
ISBN 13 : 3030105466
Total Pages : 71 pages
Book Rating : 4.0/5 (31 download)

DOWNLOAD NOW!

Book Synopsis Deep Reinforcement Learning for Wireless Networks by : F. Richard Yu

Download or read book Deep Reinforcement Learning for Wireless Networks written by F. Richard Yu and published by Springer. This book was released on 2019-01-17 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Springerbrief presents a deep reinforcement learning approach to wireless systems to improve system performance. Particularly, deep reinforcement learning approach is used in cache-enabled opportunistic interference alignment wireless networks and mobile social networks. Simulation results with different network parameters are presented to show the effectiveness of the proposed scheme. There is a phenomenal burst of research activities in artificial intelligence, deep reinforcement learning and wireless systems. Deep reinforcement learning has been successfully used to solve many practical problems. For example, Google DeepMind adopts this method on several artificial intelligent projects with big data (e.g., AlphaGo), and gets quite good results.. Graduate students in electrical and computer engineering, as well as computer science will find this brief useful as a study guide. Researchers, engineers, computer scientists, programmers, and policy makers will also find this brief to be a useful tool.