Alpha Zero
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Game Changer
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Author : Matthew Sadler
language : en
Publisher: New In Chess,Csi
Release Date : 2019
Game Changer written by Matthew Sadler and has been published by New In Chess,Csi this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Artificial intelligence categories.
Presents the story behind the self-learning artificial intelligence system with its stunning chess skills
Alpha Zero
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Author : Arthur Stone
language : en
Publisher:
Release Date : 2020-12-20
Alpha Zero written by Arthur Stone and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-20 with categories.
I should not exist.All children like me are stillborn, or die in infancy. Those who cannot grow stronger, die. No empty child has ever reached a year of age, yet I am now thirteen.It has been a long and miserable thirteen years, where the best I can manage to do is walk with difficulty. Sometimes, I cannot even manage that.My clan has paid dearly for every minute of my life. And money is not so easy to obtain, here at the edge of civilization.Perhaps I might have lived in this state for many years. A cripple, strong in mind but feeble in body. But when some unexpected guests came to our estate, everything changed. I would die at last - or, I would learn to survive on my own.
Lessons From Alphazero For Optimal Model Predictive And Adaptive Control
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Author : Dimitri Bertsekas
language : en
Publisher: Athena Scientific
Release Date : 2022-03-19
Lessons From Alphazero For Optimal Model Predictive And Adaptive Control written by Dimitri Bertsekas and has been published by Athena Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-19 with Computers categories.
The purpose of this book is to propose and develop a new conceptual framework for approximate Dynamic Programming (DP) and Reinforcement Learning (RL). This framework centers around two algorithms, which are designed largely independently of each other and operate in synergy through the powerful mechanism of Newton's method. We call these the off-line training and the on-line play algorithms; the names are borrowed from some of the major successes of RL involving games. Primary examples are the recent (2017) AlphaZero program (which plays chess), and the similarly structured and earlier (1990s) TD-Gammon program (which plays backgammon). In these game contexts, the off-line training algorithm is the method used to teach the program how to evaluate positions and to generate good moves at any given position, while the on-line play algorithm is the method used to play in real time against human or computer opponents. Both AlphaZero and TD-Gammon were trained off-line extensively using neural networks and an approximate version of the fundamental DP algorithm of policy iteration. Yet the AlphaZero player that was obtained off-line is not used directly during on-line play (it is too inaccurate due to approximation errors that are inherent in off-line neural network training). Instead a separate on-line player is used to select moves, based on multistep lookahead minimization and a terminal position evaluator that was trained using experience with the off-line player. The on-line player performs a form of policy improvement, which is not degraded by neural network approximations. As a result, it greatly improves the performance of the off-line player. Similarly, TD-Gammon performs on-line a policy improvement step using one-step or two-step lookahead minimization, which is not degraded by neural network approximations. To this end it uses an off-line neural network-trained terminal position evaluator, and importantly it also extends its on-line lookahead by rollout (simulation with the one-step lookahead player that is based on the position evaluator). Significantly, the synergy between off-line training and on-line play also underlies Model Predictive Control (MPC), a major control system design methodology that has been extensively developed since the 1980s. This synergy can be understood in terms of abstract models of infinite horizon DP and simple geometrical constructions, and helps to explain the all-important stability issues within the MPC context. An additional benefit of policy improvement by approximation in value space, not observed in the context of games (which have stable rules and environment), is that it works well with changing problem parameters and on-line replanning, similar to indirect adaptive control. Here the Bellman equation is perturbed due to the parameter changes, but approximation in value space still operates as a Newton step. An essential requirement here is that a system model is estimated on-line through some identification method, and is used during the one-step or multistep lookahead minimization process. In this monograph we aim to provide insights (often based on visualization), which explain the beneficial effects of on-line decision making on top of off-line training. In the process, we will bring out the strong connections between the artificial intelligence view of RL, and the control theory views of MPC and adaptive control. Moreover, we will show that in addition to MPC and adaptive control, our conceptual framework can be effectively integrated with other important methodologies such as multiagent systems and decentralized control, discrete and Bayesian optimization, and heuristic algorithms for discrete optimization. One of our principal aims is to show, through the algorithmic ideas of Newton's method and the unifying principles of abstract DP, that the AlphaZero/TD-Gammon methodology of approximation in value space and rollout applies very broadly to deterministic and stochastic optimal control problems. Newton's method here is used for the solution of Bellman's equation, an operator equation that applies universally within DP with both discrete and continuous state and control spaces, as well as finite and infinite horizon.
Digital Business And Electronic Commerce
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Author : Bernd W. Wirtz
language : en
Publisher: Springer Nature
Release Date :
Digital Business And Electronic Commerce written by Bernd W. Wirtz and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Deep Reinforcement Learning
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Author : Aske Plaat
language : en
Publisher: Springer Nature
Release Date : 2022-06-10
Deep Reinforcement Learning written by Aske Plaat and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-10 with Computers categories.
Deep reinforcement learning has attracted considerable attention recently. Impressive results have been achieved in such diverse fields as autonomous driving, game playing, molecular recombination, and robotics. In all these fields, computer programs have taught themselves to understand problems that were previously considered to be very difficult. In the game of Go, the program AlphaGo has even learned to outmatch three of the world’s leading players.Deep reinforcement learning takes its inspiration from the fields of biology and psychology. Biology has inspired the creation of artificial neural networks and deep learning, while psychology studies how animals and humans learn, and how subjects’ desired behavior can be reinforced with positive and negative stimuli. When we see how reinforcement learning teaches a simulated robot to walk, we are reminded of how children learn, through playful exploration. Techniques that are inspired by biology and psychology work amazingly well in computers: animal behavior and the structure of the brain as new blueprints for science and engineering. In fact, computers truly seem to possess aspects of human behavior; as such, this field goes to the heart of the dream of artificial intelligence. These research advances have not gone unnoticed by educators. Many universities have begun offering courses on the subject of deep reinforcement learning. The aim of this book is to provide an overview of the field, at the proper level of detail for a graduate course in artificial intelligence. It covers the complete field, from the basic algorithms of Deep Q-learning, to advanced topics such as multi-agent reinforcement learning and meta learning.
Force Testing Manual For The Langley 20 Inch Mach 6 Tunnel
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Author : J. Wayne Keyes
language : en
Publisher:
Release Date : 1977
Force Testing Manual For The Langley 20 Inch Mach 6 Tunnel written by J. Wayne Keyes and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1977 with categories.
Cognitive Analytics And Reinforcement Learning
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Author : Elakkiya R.
language : en
Publisher: John Wiley & Sons
Release Date : 2024-04-10
Cognitive Analytics And Reinforcement Learning written by Elakkiya R. 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 2024-04-10 with Technology & Engineering categories.
COGNITIVE ANALYTICS AND REINFORCEMENT LEARNING The combination of cognitive analytics and reinforcement learning is a transformational force in the field of modern technological breakthroughs, reshaping the decision-making, problem-solving, and innovation landscape; this book offers an examination of the profound overlap between these two fields and illuminates its significant consequences for business, academia, and research. Cognitive analytics and reinforcement learning are pivotal branches of artificial intelligence. They have garnered increased attention in the research field and industry domain on how humans perceive, interpret, and respond to information. Cognitive science allows us to understand data, mimic human cognitive processes, and make informed decisions to identify patterns and adapt to dynamic situations. The process enhances the capabilities of various applications. Readers will uncover the latest advancements in AI and machine learning, gaining valuable insights into how these technologies are revolutionizing various industries, including transforming healthcare by enabling smarter diagnosis and treatment decisions, enhancing the efficiency of smart cities through dynamic decision control, optimizing debt collection strategies, predicting optimal moves in complex scenarios like chess, and much more. With a focus on bridging the gap between theory and practice, this book serves as an invaluable resource for researchers and industry professionals seeking to leverage cognitive analytics and reinforcement learning to drive innovation and solve complex problems. The book’s real strength lies in bridging the gap between theoretical knowledge and practical implementation. It offers a rich tapestry of use cases and examples. Whether you are a student looking to gain a deeper understanding of these cutting-edge technologies, an AI practitioner seeking innovative solutions for your projects, or an industry leader interested in the strategic applications of AI, this book offers a treasure trove of insights and knowledge to help you navigate the complex and exciting world of cognitive analytics and reinforcement learning. Audience The book caters to a diverse audience that spans academic researchers, AI practitioners, data scientists, industry leaders, tech enthusiasts, and educators who associate with artificial intelligence, data analytics, and cognitive sciences.
Artificial Intelligence For Dummies
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Author : John Paul Mueller
language : en
Publisher: John Wiley & Sons
Release Date : 2021-11-24
Artificial Intelligence For Dummies written by John Paul Mueller 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 2021-11-24 with Computers categories.
Forget far-away dreams of the future. Artificial intelligence is here now! Every time you use a smart device or some sort of slick technology—be it a smartwatch, smart speaker, security alarm, or even customer service chat box—you’re engaging with artificial intelligence (AI). If you’re curious about how AI is developed—or question whether AI is real—Artificial Intelligence For Dummies holds the answers you’re looking for. Starting with a basic definition of AI and explanations of data use, algorithms, special hardware, and more, this reference simplifies this complex topic for anyone who wants to understand what operates the devices we can’t live without. This book will help you: Separate the reality of artificial intelligence from the hype Know what artificial intelligence can accomplish and what its limits are Understand how AI speeds up data gathering and analysis to help you make informed decisions more quickly See how AI is being used in hardware applications like drones, robots, and vehicles Know where AI could be used in space, medicine, and communication fields sooner than you think Almost 80 percent of the devices you interact with every day depend on some sort of AI. And although you don’t need to understand AI to operate your smart speaker or interact with a bot, you’ll feel a little smarter—dare we say more intelligent—when you know what’s going on behind the scenes. So don’t wait. Pick up this popular guide to unlock the secrets of AI today!
Fuzzy Probabilities And Fuzzy Sets For Web Planning
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Author : James J. Buckley
language : en
Publisher: Springer
Release Date : 2012-09-23
Fuzzy Probabilities And Fuzzy Sets For Web Planning written by James J. Buckley and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-23 with Mathematics categories.
1.1 Introduction This book is written in five major divisions. The first part is the introduc tory chapters consisting of Chapters 1-3. In part two, Chapters 4-10, we use fuzzy probabilities to model a fuzzy queuing system . We switch to employ ing fuzzy arrival rates and fuzzy service rates to model the fuzzy queuing system in part three in Chapters 11 and 12. Optimization models comprise part four in Chapters 13-17. The final part has a brief summary and sug gestions for future research in Chapter 18, and a summary of our numerical methods for calculating fuzzy probabilities, values of objective functions in fuzzy optimization, etc., is in Chapter 19. First we need to be familiar with fuzzy sets. All you need to know about fuzzy sets for this book comprises Chapter 2. Two other items relating to fuzzy sets, needed in Chapters 13-17, are also in Chapter 2: (1) how we plan to handle the maximum/minimum of a fuzzy set; and (2) how we will rank a finite collection of fuzzy numbers from smallest to largest.
Smart Computing
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Author : Mohammad Ayoub Khan
language : en
Publisher: CRC Press
Release Date : 2021-06-22
Smart Computing written by Mohammad Ayoub Khan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-22 with Computers categories.
The field of SMART technologies is an interdependent discipline. It involves the latest burning issues ranging from machine learning, cloud computing, optimisations, modelling techniques, Internet of Things, data analytics, and Smart Grids among others, that are all new fields. It is an applied and multi-disciplinary subject with a focus on Specific, Measurable, Achievable, Realistic & Timely system operations combined with Machine intelligence & Real-Time computing. It is not possible for any one person to comprehensively cover all aspects relevant to SMART Computing in a limited-extent work. Therefore, these conference proceedings address various issues through the deliberations by distinguished Professors and researchers. The SMARTCOM 2020 proceedings contain tracks dedicated to different areas of smart technologies such as Smart System and Future Internet, Machine Intelligence and Data Science, Real-Time and VLSI Systems, Communication and Automation Systems. The proceedings can be used as an advanced reference for research and for courses in smart technologies taught at graduate level.