reinforcement learning

reinforcement learningの商品一覧です。「Reinforcement Learning for Finance: A Python-Based Introduction (English Edition)」(￥9,876)や「洋書 Paperback, Artificial Intelligence: An Essential Beginner s Guide to AI, Machine Learning, Robotics, The Internet of Things, Neural Networks, Deep Learning, Reinforcement Learning, and Our Future」(￥4,496)、「Reinforcement Learning, second edition: An Introduction (Adaptive Computation and Machine Learning series)」(￥16,723)など

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reinforcement learning

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洋書 Paperback, Artificial Intelligence: An Essential Beginner s Guide to AI, Machine Learning, Robotics, The Internet of Things, Neural Networks, Deep Learning, Reinforcement Learning, and Our Future

Reinforcement Learning, second edition: An Introduction (Adaptive Computation and Machine Learning series)

Reinforcement Learning and Stochastic Optimization: A Unified Framework for Sequential Decisions (English Edition)

Reinforcement Learning and Approximate Dynamic Programming for Feedback Control【電子書籍】

洋書 Springer Paperback, Reinforcement Learning: State-of-the-Art (Adaptation, Learning, and Optimization (12))

PyTorch 1.x Reinforcement Learning Cookbook Over 60 recipes to design, develop, and deploy self-learning AI models using Python【電子書籍】 Yuxi (Hayden) Liu

Reinforcement Learning, second edition An Introduction【電子書籍】 Richard S. Sutton

Handbook of Reinforcement Learning and Control【電子書籍】

PyTorch Deep Learning Hands-On Build CNNs, RNNs, GANs, reinforcement learning, and more, quickly and easily【電子書籍】 Sherin Thomas

Reinforcement Learning in the Ridesharing Marketplace【電子書籍】 Zhiwei (Tony) Qin

Stability Enhancement Methods of Inverters Based on Lyapunov Function, Predictive Control, and Reinforcement Learning【電子書籍】 Xin Zhang

Reinforcement Learning: Industrial Applications of Intelligent Agents

Multi-Agent Reinforcement Learning: Foundations and Modern Approaches

TensorFlow Deep Learning Projects 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning【電子書籍】 Alexey Grigorev

Advanced Deep Learning with Keras Apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more【電子書籍】 Rowel Atienza

Artificial Intelligence with Python Master Deep Learning, Reinforcement Learning, LLMs, and Modern AI Applications【電子書籍】 Alberto Artasanchez

Deep Reinforcement Learning Hands-On: Apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more, 2nd Edition

【中古】【輸入品未使用】Deep Reinforcement Learning: Fundamentals カンマ Research and Applications

Deep Reinforcement Learning Hands-On: A practical and easy-to-follow guide to RL from Q-learning and DQNs to PPO and RLHF (English Edition)

Reinforcement Learning With Open AI, TensorFlow and Keras Using Python【電子書籍】 Abhishek Nandy

Deep Reinforcement Learning Fundamentals, Research and Applications【電子書籍】

Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games【電子書籍】 Bosen Lian

Hands-On Deep Learning for Games Leverage the power of neural networks and reinforcement learning to build intelligent games【電子書籍】 Micheal Lanham

Reinforcement Learning and Stochastic Optimization A Unified Framework for Sequential Decisions【電子書籍】 Warren B. Powell

Deep Reinforcement Learning with Python: Master classic RL, deep RL, distributional RL, inverse RL, and more with OpenAI Gym and TensorFlow, 2nd Edition

Reinforcement Learning Aktuelle Ans tze verstehen mit Beispielen in Java und Greenfoot【電子書籍】 Uwe Lorenz

Reinforcement Learning with Hybrid Quantum Approximation in the NISQ Context【電子書籍】 Leonhard Kunczik

Mathematical Foundations of Reinforcement Learning (English Edition)

Reinforcement Learning for Finance: A Python-Based Introduction (English Edition)

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価格￥9,876

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洋書 Paperback, Artificial Intelligence: An Essential Beginner s Guide to AI, Machine Learning, Robotics, The Internet of Things, Neural Networks, Deep Learning, Reinforcement Learning, and Our Future

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価格￥4,496

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*** We ship internationally, so do not use a package forwarding service. We cannot ship to a package forwarding company address because of the Japanese customs regulation. If it is shipped and customs office does not let the package go, we do not make a refund. 【注意事項】 *** 特に注意してください。 *** ・個人ではない法人・団体名義での購入はできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。・お名前にカタカナが入っている場合法人である可能性が高いため当店システムから自動保留します。カタカナで記載が必要な場合はカタカナ変わりローマ字で記載してください。・お名前またはご住所が法人・団体名義（XX株式会社等）、商店名などを含めている場合、または電話番号が個人のものではない場合、税関から法人名義でみなされますのでご注意ください。・転送サービス会社への発送もできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。 *** ・注文後品切れや価格変動でキャンセルされる場合がございますので予めご了承願います。・当店でご購入された商品は、原則として、「個...

Reinforcement Learning, second edition: An Introduction (Adaptive Computation and Machine Learning series)

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価格￥16,723

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Reinforcement Learning and Stochastic Optimization: A Unified Framework for Sequential Decisions (English Edition)

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価格￥25,058

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Reinforcement Learning and Approximate Dynamic Programming for Feedback Control【電子書籍】

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価格￥20,282

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＜p＞Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single player decision and control and multi-player games. Edited by the pioneers of RL and ADP research, the book brings together ideas and methods from many fields and provides an important and timely guidance on controlling a wide variety of systems, such as robots, industrial processes, and economic decision-making.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。

洋書 Springer Paperback, Reinforcement Learning: State-of-the-Art (Adaptation, Learning, and Optimization (12))

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PyTorch 1.x Reinforcement Learning Cookbook Over 60 recipes to design, develop, and deploy self-learning AI models using Python【電子書籍】[ Yuxi (Hayden) Liu ]

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価格￥4,151

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＜p＞＜strong＞Implement reinforcement learning techniques and algorithms with the help of real-world examples and recipes＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Use PyTorch 1.x to design and build self-learning artificial intelligence (AI) models＜/li＞＜li＞Implement RL algorithms to solve control and optimization challenges faced by data scientists today＜/li＞＜li＞Apply modern RL libraries to simulate a controlled environment for your projects＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞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.＜/p＞＜p＞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-...

Reinforcement Learning, second edition An Introduction【電子書籍】[ Richard S. Sutton ]

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価格￥14,826

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＜p＞＜strong＞The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence.＜/strong＞＜/p＞＜p＞Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In ＜em＞Reinforcement Learning＜/em＞, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics.＜/p＞＜p＞Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case f...

Handbook of Reinforcement Learning and Control【電子書籍】

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価格￥27,955

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＜p＞This handbook presents state-of-the-art research in reinforcement learning, focusing on its applications in the control and game theory of dynamic systems and future directions for related research and technology.＜/p＞＜p＞The contributions gathered in this book deal with challenges faced when using learning and adaptation methods to solve academic and industrial problems, such as optimization in dynamic environments with single and multiple agents, convergence and performance analysis, and online implementation. They explore means by which these difficulties can be solved, and cover a wide range of related topics including:＜/p＞＜ul＞＜li＞deep learning;＜/li＞＜li＞artificial intelligence;＜/li＞＜li＞applications of game theory;＜/li＞＜li＞mixed modality learning; and＜/li＞＜li＞multi-agent reinforcement learning.＜/li＞＜/ul＞＜p＞Practicing engineers and scholars in the field of machine learning, game theory, and autonomous control will find the ＜em＞Handbook...

PyTorch Deep Learning Hands-On Build CNNs, RNNs, GANs, reinforcement learning, and more, quickly and easily【電子書籍】[ Sherin Thomas ]

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価格￥4,151

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＜p＞＜strong＞Hands-on projects cover all the key deep learning methods built step-by-step in PyTorch＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Internals and principles of PyTorch＜/li＞＜li＞Implement key deep learning methods in PyTorch: CNNs, GANs, RNNs, reinforcement learning, and more＜/li＞＜li＞Build deep learning workflows and take deep learning models from prototyping to production＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞PyTorch Deep Learning Hands-On is a book for engineers who want a fast-paced guide to doing deep learning work with Pytorch. It is not an academic textbook and does not try to teach deep learning principles. The book will help you most if you want to get your hands dirty and put PyTorch to work quickly.＜/p＞＜p＞PyTorch Deep Learning Hands-On shows how to implement the major deep learning architectures in PyTorch. It covers neural networks, computer vision, CNNs, natural language processing (RNN), GANs, and reinforcement learnin...

Reinforcement Learning in the Ridesharing Marketplace【電子書籍】[ Zhiwei (Tony) Qin ]

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価格￥4,861

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＜p＞This book provides a comprehensive overview of reinforcement learning for ridesharing applications. The authors first lay out the fundamentals of the ridesharing system architectures and review the basics of reinforcement learning, including the major applicable algorithms. The book describes the research problems associated with the various aspects of a ridesharing system and discusses the existing reinforcement learning approaches for solving them. The authors survey the existing research on each problem, and then examine specific case studies. The book also includes a review of two of methods closely related to reinforcement learning: approximate dynamic programming and model-predictive control.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。

Stability Enhancement Methods of Inverters Based on Lyapunov Function, Predictive Control, and Reinforcement Learning【電子書籍】[ Xin Zhang ]

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価格￥15,800

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＜p＞This book introduces a family of large-signal stability-based control methods for different power inverters (grid-connected inverter, standalone inverter, single-phase inverter, and three-phase inverter) in practical applications. Power inverters have stability issues, which include the inverter's own instability as well as the inverter's instability in relation to the other power electronic devices in the system (i.e., weak grid and the EMI filter). Most of the stability analyses and solutions are based on small-signal stability technology. Unfortunately, in actuality, the majority of practical instability concerns in power inverter systems are large-signal stability problems, which, when compared to small-signal stability problems, can cause substantial damage to electrical equipment.＜/p＞＜p＞As a result, researchers must conduct a comprehensive investigation of the large-signal stability challenge and solutions for power inverters. This book can be used as a reference for...

Reinforcement Learning: Industrial Applications of Intelligent Agents

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価格￥8,037

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Multi-Agent Reinforcement Learning: Foundations and Modern Approaches

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価格￥11,139

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TensorFlow Deep Learning Projects 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning【電子書籍】[ Alexey Grigorev ]

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価格￥5,155

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＜p＞Leverage the power of Tensorflow to design deep learning systems for a variety of real-world scenarios About This Book ? Build efficient deep learning pipelines using the popular Tensorflow framework ? Train neural networks such as ConvNets, generative models, and LSTMs ? Includes projects related to Computer Vision, stock prediction, chatbots and more Who This Book Is For This book is for data scientists, machine learning developers as well as deep learning practitioners, who want to build interesting deep learning projects that leverage the power of Tensorflow. Some understanding of machine learning and deep learning, and familiarity with the TensorFlow framework is all you need to get started with this book. What You Will Learn ? Set up the TensorFlow environment for deep learning ? Construct your own ConvNets for effective image processing ? Use LSTMs for image caption generation ? Forecast stock prediction accurately with an LSTM architecture ? Learn what semantic matching...

Advanced Deep Learning with Keras Apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more【電子書籍】[ Rowel Atienza ]

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価格￥3,787

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＜p＞＜b＞Understanding and coding advanced deep learning algorithms with the most intuitive deep learning library in existence＜/b＞＜/p＞＜h2＞Key Features＜/h2＞＜ul＞＜li＞Explore the most advanced deep learning techniques that drive modern AI results＜/li＞＜li＞Implement deep neural networks, autoencoders, GANs, VAEs, and deep reinforcement learning＜/li＞＜li＞A wide study of GANs, including Improved GANs, Cross-Domain GANs, and Disentangled Representation GANs＜/li＞＜/ul＞＜h2＞Book Description＜/h2＞Recent developments in deep learning, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Deep Reinforcement Learning (DRL) are creating impressive AI results in our news headlines - such as AlphaGo Zero beating world chess champions, and generative AI that can create art paintings that sell for over $400k because they are so human-like. Advanced Deep Learning with Keras is a comprehensive guide to the advanced deep learning techniques availab...

Artificial Intelligence with Python Master Deep Learning, Reinforcement Learning, LLMs, and Modern AI Applications【電子書籍】[ Alberto Artasanchez ]

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価格￥3,444

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＜p＞＜b＞Build AI applications using cutting-edge frameworks like PyTorch, TensorFlow, and Hugging Face Purchase of the print or Kindle book includes a free PDF eBook＜/b＞＜/p＞＜h2＞Key Features＜/h2＞＜ul＞＜li＞Large Language Models (LLMs) like GPT, BERT, and Llama 2 for real-world AI projects＜/li＞＜li＞Advanced AI topics, including MLOps, multimodal AI, and Edge AI deployment＜/li＞＜li＞Hands-on projects in chatbots, autonomous agents, generative AI, and time-series forecasting＜/li＞＜/ul＞＜h2＞Book Description＜/h2＞Artificial Intelligence with Python, Third Edition is a complete, hands-on guide that takes you from the foundations of AI to mastering cutting-edge techniques, including Large Language Models (LLMs), Reinforcement Learning, and MLOps. This fully updated edition ensures you stay ahead with the latest AI innovations. You'll explore machine learning algorithms, neural networks, and state-of-the-art deep learning architectures like transformers and diffusion mod...

Deep Reinforcement Learning Hands-On: Apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more, 2nd Edition

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【中古】【輸入品・未使用】Deep Reinforcement Learning: Fundamentals%カンマ% Research and Applications

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価格￥87,974

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【中古】【輸入品・未使用】Deep Reinforcement Learning: Fundamentals%カンマ% Research and Applications【メーカー名】Springer【メーカー型番】【ブランド名】Springer【商品説明】Deep Reinforcement Learning: Fundamentals%カンマ% Research and Applications当店では初期不良に限り、商品到着から7日間は返品を受付けております。こちらは海外販売用に買取り致しました未使用品です。買取り致しました為、中古扱いとしております。他モールとの併売品の為、完売の際はご連絡致しますのでご了承下さい。速やかにご返金させて頂きます。ご注文からお届けまで1、ご注文⇒ご注文は24時間受け付けております。2、注文確認⇒ご注文後、当店から注文確認メールを送信します。3、配送⇒当店海外倉庫から取り寄せの場合は10〜30日程度でのお届けとなります。国内到着後、発送の際に通知にてご連絡致します。国内倉庫からの場合は3〜7日でのお届けとなります。　※離島、北海道、九州、沖縄は遅れる場合がございます。予めご了承下さい。お電話でのお問合せは少人数で運営の為受け付けておりませんので、メールにてお問合せお願い致します。営業時間　月〜金　10:00〜17:00お客...

Deep Reinforcement Learning Hands-On: A practical and easy-to-follow guide to RL from Q-learning and DQNs to PPO and RLHF (English Edition)

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Reinforcement Learning With Open AI, TensorFlow and Keras Using Python【電子書籍】[ Abhishek Nandy ]

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価格￥7,900

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＜p＞Master reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve and then gain a clear picture of how they are inter-related. You’ll then work with theories related to reinforcement learning and see the concepts that build up the reinforcement learning process.＜/p＞＜p＞＜em＞Reinforcement Learning＜/em＞ discusses algorithm implementations important for reinforcement learning, including Markov’s Decision process and Semi Markov Decision process. The next section shows you how to get started with Open AI before looking at Open AI Gym. You’ll then learn about Swarm Intelligence with Python in terms of reinforcement learning.＜/p＞＜p＞The last part of the book starts with the TensorFlow environment and gives an outline of how reinforcement learning can be applied to TensorFlow. There’s also coverage of Keras, a framework that can be used with reinforcement learning. Finally, you'll delve into Google’s ...

強化学習（第2版）

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Deep Reinforcement Learning Fundamentals, Research and Applications【電子書籍】

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価格￥21,878

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＜p＞Deep reinforcement learning (DRL) is the combination of reinforcement learning (RL) and deep learning. It has been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine, and famously contributed to the success of AlphaGo. Furthermore, it opens up numerous new applications in domains such as healthcare, robotics, smart grids and finance.＜/p＞＜p＞Divided into three main parts, this book provides a comprehensive and self-contained introduction to DRL. The first part introduces the foundations of deep learning, reinforcement learning (RL) and widely used deep RL methods and discusses their implementation. The second part covers selected DRL research topics, which are useful for those wanting to specialize in DRL research. To help readers gain a deep understanding of DRL and quickly apply the techniques in practice, the third part presents mass applications, such as the intelligent transportation system and learning to run, wi...

Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games【電子書籍】[ Bosen Lian ]

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価格￥17,016

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＜p＞＜em＞Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games＜/em＞ develops its specific learning techniques, motivated by application to autonomous driving and microgrid systems, with breadth and depth: integral reinforcement learning (RL) achieves model-free control without system estimation compared with system identification methods and their inevitable estimation errors; novel inverse RL methods fill a gap that will help them to attract readers interested in finding data-driven model-free solutions for inverse optimization and optimal control, imitation learning and autonomous driving among other areas.＜/p＞＜p＞Graduate students will find that this book offers a thorough introduction to integral and inverse RL for feedback control related to optimal regulation and tracking, disturbance rejection, and multiplayer and multiagent systems. For researchers, it provides a combination of theoretical analysis, rigorous algorithms, and a wide-ranging ...

Hands-On Deep Learning for Games Leverage the power of neural networks and reinforcement learning to build intelligent games【電子書籍】[ Micheal Lanham ]

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価格￥4,151

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＜p＞＜strong＞Understand the core concepts of deep learning and deep reinforcement learning by applying them to develop games＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Apply the power of deep learning to complex reasoning tasks by building a Game AI＜/li＞＜li＞Exploit the most recent developments in machine learning and AI for building smart games＜/li＞＜li＞Implement deep learning models and neural networks with Python＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞The number of applications of deep learning and neural networks has multiplied in the last couple of years. Neural nets has enabled significant breakthroughs in everything from computer vision, voice generation, voice recognition and self-driving cars. Game development is also a key area where these techniques are being applied. This book will give an in depth view of the potential of deep learning and neural networks in game development.＜/p＞＜p＞We will take a look at the foundations of multi-la...

Reinforcement Learning and Stochastic Optimization A Unified Framework for Sequential Decisions【電子書籍】[ Warren B. Powell ]

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価格￥19,969

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＜p＞＜strong＞REINFORCEMENT LEARNING AND STOCHASTIC OPTIMIZATION＜/strong＞＜/p＞＜p＞＜strong＞Clearing the jungle of stochastic optimization＜/strong＞＜/p＞＜p＞Sequential decision problems, which consist of “decision, information, decision, information,” are ubiquitous, spanning virtually every human activity ranging from business applications, health (personal and public health, and medical decision making), energy, the sciences, all fields of engineering, finance, and e-commerce. The diversity of applications attracted the attention of at least 15 distinct fields of research, using eight distinct notational systems which produced a vast array of analytical tools. A byproduct is that powerful tools developed in one community may be unknown to other communities.＜/p＞＜p＞＜em＞Reinforcement Learning and Stochastic Optimization＜/em＞ offers a single canonical framework that can model any sequential decision problem using five core components: state variables, decision varia...

Deep Reinforcement Learning with Python: Master classic RL, deep RL, distributional RL, inverse RL, and more with OpenAI Gym and TensorFlow, 2nd Edition

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価格￥6,552

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Reinforcement Learning Aktuelle Ans?tze verstehen ? mit Beispielen in Java und Greenfoot【電子書籍】[ Uwe Lorenz ]

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価格￥3,179

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＜p＞In uralten Spielen wie Schach oder Go k?nnen sich die brillantesten Spieler verbessern, indem sie die von einer Maschine produzierten Strategien studieren. Robotische Systeme ?ben ihre Bewegungen selbst. In Arcade Games erreichen lernf?hige Agenten innerhalb weniger Stunden ?bermenschliches Niveau. Wie funktionieren diese spektakul?ren Algorithmen des best?rkenden Lernens? Mit gut verst?ndlichen Erkl?rungen und ?bersichtlichen Beispielen in Java und Greenfoot k?nnen Sie sich die Prinzipien des best?rkenden Lernens aneignen und in eigenen intelligenten Agenten anwenden. Greenfoot (M.K?lling, King’s College London) und das Hamster-Modell (D.Bohles, Universit?t Oldenburg) sind einfache, aber auch m?chtige didaktische Werkzeuge, die entwickelt wurden, um Grundkonzepte der Programmierung zu vermitteln. Wir werden Figuren wie den Java-Hamster zu lernf?higen Agenten machen, die eigenst?ndig ihre Umgebung erkunden. Die zweite Auflage enth?lt neue Themen wie "Genetische Algorithmen" und...

Reinforcement Learning with Hybrid Quantum Approximation in the NISQ Context【電子書籍】[ Leonhard Kunczik ]

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価格￥10,331

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＜p＞This book explores the combination of Reinforcement Learning and Quantum Computing in the light of complex attacker-defender scenarios. Reinforcement Learning has proven its capabilities in different challenging optimization problems and is now an established method in Operations Research. However, complex attacker-defender scenarios have several characteristics that challenge Reinforcement Learning algorithms, requiring enormous computational power to obtain the optimal solution.＜/p＞＜p＞The upcoming field of Quantum Computing is a promising path for solving computationally complex problems. Therefore, this work explores a hybrid quantum approach to policy gradient methods in Reinforcement Learning. It proposes a novel quantum REINFORCE algorithm that enhances its classical counterpart by Quantum Variational Circuits. The new algorithm is compared to classical algorithms regarding the convergence speed and memory usage on several attacker-defender scenarios with increasing ...

Mathematical Foundations of Reinforcement Learning (English Edition)

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価格￥13,878

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