Download or read book Break the One Armed Bandits written by Frank Scoblete and published by Bonus Books, Inc.. This book was released on 1994 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of America's bestselling gaming authors has written the definitive book on slot machines. Players can learn what makes some machines "player-friendly" and other machines "player-deadly" and how to distinguish between them. In the land of the one-armed bandits, this new book is the road map slot players need.
Download or read book Introduction to Multi Armed Bandits written by Aleksandrs Slivkins and published by . This book was released on 2019-10-31 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-armed bandits is a rich, multi-disciplinary area that has been studied since 1933, with a surge of activity in the past 10-15 years. This is the first book to provide a textbook like treatment of the subject.
Download or read book One Armed Bandit written by Julius Blair and published by JB Comics. This book was released on 2022-05-30 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: One Armed Bandit Jayden, a young wartorn soldier given super powers by a ruling elite class he was made to protect must go against all of his former friends and allies to restore the balance of power.One Armed Bandit is an action drama set in the future, in a world divided, where all traces of history have been lost. Where superhuman abilities are created by the wealthy, fueled by their greed, their lust for power and their thirst for everlasting life. One man, Jayden Wright, fights to restore balance to the world, whilst others fight to destroy it.
Download or read book Regret Analysis of Stochastic and Nonstochastic Multi armed Bandit Problems written by Sébastien Bubeck and published by Now Pub. This book was released on 2012 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this monograph, the focus is on two extreme cases in which the analysis of regret is particularly simple and elegant: independent and identically distributed payoffs and adversarial payoffs. Besides the basic setting of finitely many actions, it analyzes some of the most important variants and extensions, such as the contextual bandit model.
Download or read book Bandit Algorithms written by Tor Lattimore and published by Cambridge University Press. This book was released on 2020-07-16 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and rigorous introduction for graduate students and researchers, with applications in sequential decision-making problems.
Download or read book Bandit Algorithms for Website Optimization written by John Myles White and published by "O'Reilly Media, Inc.". This book was released on 2012-12-10 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: When looking for ways to improve your website, how do you decide which changes to make? And which changes to keep? This concise book shows you how to use Multiarmed Bandit algorithms to measure the real-world value of any modifications you make to your site. Author John Myles White shows you how this powerful class of algorithms can help you boost website traffic, convert visitors to customers, and increase many other measures of success. This is the first developer-focused book on bandit algorithms, which were previously described only in research papers. You’ll quickly learn the benefits of several simple algorithms—including the epsilon-Greedy, Softmax, and Upper Confidence Bound (UCB) algorithms—by working through code examples written in Python, which you can easily adapt for deployment on your own website. Learn the basics of A/B testing—and recognize when it’s better to use bandit algorithms Develop a unit testing framework for debugging bandit algorithms Get additional code examples written in Julia, Ruby, and JavaScript with supplemental online materials
Download or read book Lucky Luke Volume 33 The One Armed Bandit written by Morris and published by Cinebook. This book was released on 2013-03-25T00:00:00+01:00 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brothers Adolph and Arthur Caille are mechanical geniuses. They’ve just created one of the first slot machines and have presented it to their local senator, a notorious gambler. Much taken with the device, he agrees to send them on a tour of American cities to test the machine’s popularity. And, to escort them on this dangerous journey, he calls on his old friend Lucky Luke... So begins the wacky tale of how the one-armed bandit conquered the West!
Download or read book One armed Bandit written by Russ Kidd and published by Macmillan Reference USA. This book was released on 1991 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: Western. One armed, ex-confederate soldier Luke Starr rattles a crooked lawman, a Yankee and Mexicans.
Download or read book Slot Machines and Coin op Games written by Bill Kurtz and published by Booksales. This book was released on 1991 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first mass-market book to relate the history of coin-operated game machines. The book will appeal to the collector, but the general approach is nostalgic rather than technical. Contains slot machines, novelty arcade games, gun and rifle games, bowling machines, baseball machines, pinball machines, video games, owning your own machines, and the future of coin-operated games. 150 color illustrations.
Download or read book One Armed Cowboy written by E. L. Pond and published by . This book was released on 2010-01-01 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Bandit problems written by Donald A. Berry and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our purpose in writing this monograph is to give a comprehensive treatment of the subject. We define bandit problems and give the necessary foundations in Chapter 2. Many of the important results that have appeared in the literature are presented in later chapters; these are interspersed with new results. We give proofs unless they are very easy or the result is not used in the sequel. We have simplified a number of arguments so many of the proofs given tend to be conceptual rather than calculational. All results given have been incorporated into our style and notation. The exposition is aimed at a variety of types of readers. Bandit problems and the associated mathematical and technical issues are developed from first principles. Since we have tried to be comprehens ive the mathematical level is sometimes advanced; for example, we use measure-theoretic notions freely in Chapter 2. But the mathema tically uninitiated reader can easily sidestep such discussion when it occurs in Chapter 2 and elsewhere. We have tried to appeal to graduate students and professionals in engineering, biometry, econ omics, management science, and operations research, as well as those in mathematics and statistics. The monograph could serve as a reference for professionals or as a telA in a semester or year-long graduate level course.
Download or read book The One armed Cook written by Cynthia Stevens Graubart and published by Meredith Books. This book was released on 2004 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Quick and easy recipes, smart meal plans, and savvy advice for new (and not-so-new) moms"--Cover.
Download or read book Multi armed Bandit Allocation Indices written by John Gittins and published by John Wiley & Sons. This book was released on 2011-02-18 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 1989 the first edition of this book set out Gittins' pioneering index solution to the multi-armed bandit problem and his subsequent investigation of a wide of sequential resource allocation and stochastic scheduling problems. Since then there has been a remarkable flowering of new insights, generalizations and applications, to which Glazebrook and Weber have made major contributions. This second edition brings the story up to date. There are new chapters on the achievable region approach to stochastic optimization problems, the construction of performance bounds for suboptimal policies, Whittle's restless bandits, and the use of Lagrangian relaxation in the construction and evaluation of index policies. Some of the many varied proofs of the index theorem are discussed along with the insights that they provide. Many contemporary applications are surveyed, and over 150 new references are included. Over the past 40 years the Gittins index has helped theoreticians and practitioners to address a huge variety of problems within chemometrics, economics, engineering, numerical analysis, operational research, probability, statistics and website design. This new edition will be an important resource for others wishing to use this approach.
Download or read book American Saloons written by Roger Kislingbury and published by . This book was released on 2015-04-01 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book PyTorch 1 x Reinforcement Learning Cookbook written by Yuxi (Hayden) Liu and published by Packt Publishing Ltd. This book was released on 2019-10-31 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Implement reinforcement learning techniques and algorithms with the help of real-world examples and recipes Key FeaturesUse PyTorch 1.x to design and build self-learning artificial intelligence (AI) modelsImplement RL algorithms to solve control and optimization challenges faced by data scientists todayApply modern RL libraries to simulate a controlled environment for your projectsBook Description Reinforcement learning (RL) is a branch of machine learning that has gained popularity in recent times. It allows you to train AI models that learn from their own actions and optimize their behavior. PyTorch has also emerged as the preferred tool for training RL models because of its efficiency and ease of use. With this book, you'll explore the important RL concepts and the implementation of algorithms in PyTorch 1.x. The recipes in the book, along with real-world examples, will help you master various RL techniques, such as dynamic programming, Monte Carlo simulations, temporal difference, and Q-learning. You'll also gain insights into industry-specific applications of these techniques. Later chapters will guide you through solving problems such as the multi-armed bandit problem and the cartpole problem using the multi-armed bandit algorithm and function approximation. You'll also learn how to use Deep Q-Networks to complete Atari games, along with how to effectively implement policy gradients. Finally, you'll discover how RL techniques are applied to Blackjack, Gridworld environments, internet advertising, and the Flappy Bird game. By the end of this book, you'll have developed the skills you need to implement popular RL algorithms and use RL techniques to solve real-world problems. What you will learnUse Q-learning and the state–action–reward–state–action (SARSA) algorithm to solve various Gridworld problemsDevelop a multi-armed bandit algorithm to optimize display advertisingScale up learning and control processes using Deep Q-NetworksSimulate Markov Decision Processes, OpenAI Gym environments, and other common control problemsSelect and build RL models, evaluate their performance, and optimize and deploy themUse policy gradient methods to solve continuous RL problemsWho this book is for Machine learning engineers, data scientists and AI researchers looking for quick solutions to different reinforcement learning problems will find this book useful. Although prior knowledge of machine learning concepts is required, experience with PyTorch will be useful but not necessary.
Download or read book Hands On Reinforcement Learning for Games written by Micheal Lanham and published by Packt Publishing Ltd. This book was released on 2020-01-03 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore reinforcement learning (RL) techniques to build cutting-edge games using Python libraries such as PyTorch, OpenAI Gym, and TensorFlow Key FeaturesGet to grips with the different reinforcement and DRL algorithms for game developmentLearn how to implement components such as artificial agents, map and level generation, and audio generationGain insights into cutting-edge RL research and understand how it is similar to artificial general researchBook Description With the increased presence of AI in the gaming industry, developers are challenged to create highly responsive and adaptive games by integrating artificial intelligence into their projects. This book is your guide to learning how various reinforcement learning techniques and algorithms play an important role in game development with Python. Starting with the basics, this book will help you build a strong foundation in reinforcement learning for game development. Each chapter will assist you in implementing different reinforcement learning techniques, such as Markov decision processes (MDPs), Q-learning, actor-critic methods, SARSA, and deterministic policy gradient algorithms, to build logical self-learning agents. Learning these techniques will enhance your game development skills and add a variety of features to improve your game agent’s productivity. As you advance, you’ll understand how deep reinforcement learning (DRL) techniques can be used to devise strategies to help agents learn from their actions and build engaging games. By the end of this book, you’ll be ready to apply reinforcement learning techniques to build a variety of projects and contribute to open source applications. What you will learnUnderstand how deep learning can be integrated into an RL agentExplore basic to advanced algorithms commonly used in game developmentBuild agents that can learn and solve problems in all types of environmentsTrain a Deep Q-Network (DQN) agent to solve the CartPole balancing problemDevelop game AI agents by understanding the mechanism behind complex AIIntegrate all the concepts learned into new projects or gaming agentsWho this book is for If you’re a game developer looking to implement AI techniques to build next-generation games from scratch, this book is for you. Machine learning and deep learning practitioners, and RL researchers who want to understand how to use self-learning agents in the game domain will also find this book useful. Knowledge of game development and Python programming experience are required.
Download or read book Bandit written by Vicki Hearne and published by Skyhorse Publishing Inc.. This book was released on 2007-08-17 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Learned and brilliant and wonderful."Wall Street...
