Deep Reinforcement Learning, Hao Dong, Zihan Ding, Shanghang Zhang

Автор: Palanisamy Praveen
Название: TensorFlow 2 Reinforcement Learning Cookbook: Over 50 recipes to help you build, train, and deploy learning agents for real-world applications
ISBN: 183898254X ISBN-13(EAN): 9781838982546
Издательство: Неизвестно
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Цена: 60070.00 T
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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.

Автор: Lapan Maxim
Название: Deep Reinforcement Learning Hands-On - Second Edition
ISBN: 1838826998 ISBN-13(EAN): 9781838826994
Издательство: Неизвестно
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Цена: 98080.00 T
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Описание: With six new chapters, Deep Reinforcement Learning Hands-On Second edition is completely updated and expanded with the very latest reinforcement learning (RL) tools and techniques, providing you with an introduction to RL, as well as the hands-on ability to code intelligent learning agents to perform a range of practical tasks.

Автор: Francois-Lavet Vincent, Henderson Peter, Islam Riashat
Название: An Introduction to Deep Reinforcement Learning
ISBN: 1680835386 ISBN-13(EAN): 9781680835380
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Цена: 91040.00 T
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Описание: Provides a starting point for understanding deep reinforcement learning. Although written at a research level it provides a comprehensive and accessible introduction to deep reinforcement learning models, algorithms and techniques.

Автор: Bilgin Enes
Название: Mastering Reinforcement Learning with Python: Build next-generation, self-learning models using reinforcement learning techniques and best practices
ISBN: 1838644148 ISBN-13(EAN): 9781838644147
Издательство: Неизвестно
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Цена: 60070.00 T
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Описание: This book focuses on expert-level explanations and implementations of scalable reinforcement learning algorithms and approaches. Starting with the fundamentals, the book covers state-of-the-art methods from bandit problems to meta-reinforcement learning. You`ll also explore practical examples inspired by real-life problems from the industry.

Автор: Liu Yuxi (Hayden)
Название: PyTorch 1.0 Reinforcement Learning Cookbook
ISBN: 1838551964 ISBN-13(EAN): 9781838551964
Издательство: Неизвестно
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Цена: 53940.00 T
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Описание: This book presents practical solutions to the most common reinforcement learning problems. The recipes in this book will help you understand the fundamental concepts to develop popular RL algorithms. You will gain practical experience in the RL domain using the modern offerings of the PyTorch 1.x library.

Автор: Ciaburro Giuseppe
Название: Keras Reinforcement Learning Projects
ISBN: 1789342090 ISBN-13(EAN): 9781789342093
Издательство: Неизвестно
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Цена: 67430.00 T
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Описание: Keras Reinforcement Learning Projects book teaches you essential concept, techniques and, models of reinforcement learning using best real-world demonstrations. You will explore popular algorithms such as Markov decision process, Monte Carlo, Q-learning making you equipped with complex statistics in various projects with the help of Keras

Автор: Saito Sean, Wenzhuo Yang, Shanmugamani Rajalingappaa
Название: Python Reinforcement Learning Projects
ISBN: 1788991613 ISBN-13(EAN): 9781788991612
Издательство: Неизвестно
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Цена: 60070.00 T
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Описание: Python Reinforcement Learning Projects brings various aspects and methodologies of RL using 8 real-world projects that explore RL and will have hands-on experience with real data and artificial intelligence problems. You will learn to build self-learning models using sophisticated techniques like Q-learning, Markov models and Monte-Carlo process.

Автор: Lanham Micheal
Название: Hands-On Reinforcement Learning for Games
ISBN: 1839214937 ISBN-13(EAN): 9781839214936
Издательство: Неизвестно
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Цена: 53940.00 T
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Описание: The AI revolution is here and it is embracing games. Game developers are being challenged to enlist cutting edge AI as part of their games. In this book, you will look at the journey of building capable AI using reinforcement learning algorithms and techniques. You will learn to solve complex tasks and build next-generation games using a ...

Автор: Li, Chong Qiu, Meikang
Название: Reinforcement learning for cyber-physical systems
ISBN: 0367656639 ISBN-13(EAN): 9780367656638
Издательство: Taylor&Francis
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Цена: 45930.00 T
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Описание: This book introduces reinforcement learning, and provides novel ideas and use cases to demonstrate the benefits of using reinforcement learning for Cyber Physical Systems. Two important case studies on applying reinforcement learning to cybersecurity problems are included.

Автор: Ravichandiran, Sudharsan
Название: Hands-on reinforcement learning with python -
ISBN: 1839210680 ISBN-13(EAN): 9781839210686
Издательство: Неизвестно
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Цена: 60070.00 T
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Описание: Deep Reinforcement Learning with Python - Second Edition will help you learn reinforcement learning algorithms, techniques and architectures - including deep reinforcement learning - from scratch. This new edition is an extensive update of the original, reflecting the state-of-the-art latest thinking in reinforcement learning.

Автор: Balakrishnan Kaushik
Название: TensorFlow Reinforcement Learning Quick Start Guide
ISBN: 1789533589 ISBN-13(EAN): 9781789533583
Издательство: Неизвестно
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Цена: 33090.00 T
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Описание: This book is an essential guide for anyone interested in Reinforcement Learning. The book provides an actionable reference for Reinforcement Learning algorithms and their applications using TensorFlow and Python. It will help readers leverage the power of algorithms such as Deep Q-Network (DQN), Deep Deterministic Policy Gradients (DDPG), and ...

Автор: Li, Chong
Название: Reinforcement Learning for Cyber-Physical Systems with Cybersecurity Case Studies
ISBN: 1138543535 ISBN-13(EAN): 9781138543539
Издательство: Taylor&Francis
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Цена: 84710.00 T
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Описание: This book introduces reinforcement learning, and provides novel ideas and use cases to demonstrate the benefits of using reinforcement learning for Cyber Physical Systems. Two important case studies on applying reinforcement learning to cybersecurity problems are included.