Описание: This book is a practical, developer-oriented introduction to deep reinforcement learning (RL). Explore the theoretical concepts of RL, before discovering how deep learning (DL) methods and tools are making it possible to solve more complex and challenging problems than ever before. Apply deep RL methods to training your agent to beat arcade ...
Описание: Shows how to avoid or correct typical behaviour problems, including jumping, barking, and lead-pulling. This title covers hand-feeding; crate and potty training; and basic cues - sit, stay, come here - as well as complex goals, such as bite inhibition and water safety.
Автор: Mindess, Sidney Название: Developments in the Formulation and Reinforcement of Concrete ISBN: 0081026161 ISBN-13(EAN): 9780081026168 Издательство: Elsevier Science Рейтинг: Цена: 38739.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
In the first edition of this book, Developments in the Formulation and Reinforcement of Concrete, a number of what are often referred to as "specialty" concretes were discussed. These concretes through specialty mix design offer high physical properties and enhanced performance. The information discussed in these chapters is still relevant today, but in the ten years since the first edition was published, a number of other key areas have become increasingly important in modern concrete technology. There is now much more emphasis on sustainability within the cement and concrete industries. This requires a greater emphasis and understanding of some of the major durability problems that the scientist or engineer may encounter, such as chloride corrosion of steel, and alkali-aggregate reactions. There is also increasing use of specifications involving explicit service life requirements (100 years being common), but this is a concept that is still widely misunderstood.
In this second edition of the book all material previously covered on specialty concretes is brought fully up-to-date taking into consideration latest developments and with the addition of new chapters on supplementary cementitious materials; mass concrete; the sustainably of concrete; service life prediction; limestone cements; corrosion of steel in concrete; alkali-aggregate reactions and concrete as a multiscale material the chapters will introduce the reader to some of the most important issues facing the concrete industry today. In keeping with the previous edition, the international team of contributors, are all at the cutting edge in their own areas of research and have wide industrial experience.
With its distinguished editor and international team of contributors, Developments in the Formulation and Reinforcement of Concrete, Second Edition is a standard reference for civil and structural engineers.
Summarizes a wealth of recent research on structural concrete including material microstructure, concrete types, variation and construction techniques
Emphasizes concrete mixture design and applications in civil and structural engineering
Reviews modern concrete materials to novel construction systems, such as the precast industry and structures requiring high-performance concrete
Описание: 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 practical book shows data science and AI professionals how to perform the reinforcement process that allows a machine to learn by itself.
Описание: This cookbook will help you to gain a solid understanding of deep reinforcement learning (RL) algorithms with the help of concise, easy-to-follow implementations from scratch. You`ll learn how to implement these algorithms with minimal code and develop AI applications to solve real-world and business problems using RL.
Описание: With the help of practical examples and engaging activities, The Reinforcement Learning Workshop takes you through reinforcement learning`s core techniques and frameworks. Following a hands-on approach, it allows you to learn reinforcement learning at your own pace to develop your own intelligent applications with ease.
Автор: Lonza, Andrea Название: Reinforcement learning algorithms with python ISBN: 1789131111 ISBN-13(EAN): 9781789131116 Издательство: Неизвестно Рейтинг: Цена: 7539.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: With this book, you will understand the core concepts and techniques of reinforcement learning. You will take a look into each RL algorithm and will develop your own self-learning algorithms and models. You will optimize the algorithms for better precision, use high-speed actions and lower the risk of anomalies in your applications.
Автор: Szepesvari Czaba, Szepesvari Csaba Название: Algorithms for Reinforcement Learning ISBN: 1608454924 ISBN-13(EAN): 9781608454921 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 5694.00 р. Наличие на складе: Поставка под заказ.
Описание: Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. This book focuses on those algorithms of reinforcement learning that build on the powerful theory of dynamic programming.
Автор: Shimon Whiteson Название: Adaptive Representations for Reinforcement Learning ISBN: 3642422314 ISBN-13(EAN): 9783642422317 Издательство: Springer Рейтинг: Цена: 13677.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presenting the main results of new algorithms for reinforcement learning, this book also introduces a novel method for devising input representations as well as presenting a way to find a minimal set of features sufficient to describe the agent`s current state.
Автор: Lutz Frommberger Название: Qualitative Spatial Abstraction in Reinforcement Learning ISBN: 3642266002 ISBN-13(EAN): 9783642266003 Издательство: Springer Рейтинг: Цена: 14025.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Reinforcement learning has evolved to tackle domains that are yet to be fully understood, or are too complex for a closed description. In this book the author investigates whether suitable abstraction methods can overcome the discipline`s deficiencies.
Описание: This book will teach you all it takes to perform complex statistical computations required for Machine Learning. You will gain information on statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize your...
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