Reinforcement Learning From Scratch, Lorenz

Автор: Shengbo Eben Li
Название: Reinforcement Learning for Sequential Decision and Optimal Control
ISBN: 9811977836 ISBN-13(EAN): 9789811977831
Издательство: Springer
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Цена: 74530.00 T
Наличие на складе: Поставка под заказ.
Описание: Have you ever wondered how AlphaZero learns to defeat the top human Go players? Do you have any clues about how an autonomous driving system can gradually develop self-driving skills beyond normal drivers? What is the key that enables AlphaStar to make decisions in Starcraft, a notoriously difficult strategy game that has partial information and complex rules? The core mechanism underlying those recent technical breakthroughs is reinforcement learning (RL), a theory that can help an agent to develop the self-evolution ability through continuing environment interactions. In the past few years, the AI community has witnessed phenomenal success of reinforcement learning in various fields, including chess games, computer games and robotic control. RL is also considered to be a promising and powerful tool to create general artificial intelligence in the future. As an interdisciplinary field of trial-and-error learning and optimal control, RL resembles how humans reinforce their intelligence by interacting with the environment and provides a principled solution for sequential decision making and optimal control in large-scale and complex problems. Since RL contains a wide range of new concepts and theories, scholars may be plagued by a number of questions: What is the inherent mechanism of reinforcement learning? What is the internal connection between RL and optimal control? How has RL evolved in the past few decades, and what are the milestones? How do we choose and implement practical and effective RL algorithms for real-world scenarios? What are the key challenges that RL faces today, and how can we solve them? What is the current trend of RL research? You can find answers to all those questions in this book. The purpose of the book is to help researchers and practitioners take a comprehensive view of RL and understand the in-depth connection between RL and optimal control. The book includes not only systematic and thorough explanations of theoretical basics but also methodical guidance of practical algorithm implementations. The book intends to provide a comprehensive coverage of both classic theories and recent achievements, and the content is carefully and logically organized, including basic topics such as the main concepts and terminologies of RL, Markov decision process (MDP), Bellman’s optimality condition, Monte Carlo learning, temporal difference learning, stochastic dynamic programming, function approximation, policy gradient methods, approximate dynamic programming, and deep RL, as well as the latest advances in action and state constraints, safety guarantee, reference harmonization, robust RL, partially observable MDP, multiagent RL, inverse RL, offline RL, and so on.

Автор: Farsi, Milad,
Название: Model-based reinforcement learning :
ISBN: 111980857X ISBN-13(EAN): 9781119808572
Издательство: Wiley
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Цена: 108770.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is for researchers and students in statistics, data mining, computer science, machine learning, marketing and also practitioners who implement recommender systems. It provides an in-depth discussion of challenges encountered in deploying real-life large-scale systems and state-of-the-art solutions in personalization, explore/exploit, dimension reduction and multi-objective optimization.

Автор: Sutton, Richard S. Barto, Andrew G.
Название: Reinforcement learning
ISBN: 0262193981 ISBN-13(EAN): 9780262193986
Издательство: MIT Press
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Цена: 66930.00 T
Наличие на складе: Нет в наличии.
Описание: An account of key ideas and algorithms in reinforcement learning. The discussion ranges from the history of the field`s intellectual foundations to recent developments and applications. Areas studied include reinforcement learning problems in terms of Markov decision problems and solution methods.

Автор: Lonza, Andrea
Название: Reinforcement learning algorithms with python
ISBN: 1789131111 ISBN-13(EAN): 9781789131116
Издательство: Неизвестно
Рейтинг:
Цена: 47810.00 T
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: 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.

Автор: Dutta Sayon
Название: Reinforcement Learning with Tensorflow
ISBN: 1788835727 ISBN-13(EAN): 9781788835725
Издательство: Неизвестно
Цена: 67430.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Reinforcement learning allows you to develop intelligent, self-learning systems. This book shows you how to put the concepts of Reinforcement Learning to train efficient models.You will use popular reinforcement learning algorithms to implement use-cases in image processing and NLP, by combining the power of TensorFlow and OpenAI Gym.

Автор: Xiao
Название: Reinforcement Learning
ISBN: 9811949328 ISBN-13(EAN): 9789811949326
Издательство: Springer
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Цена: 69870.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Reinforcement Learning: Theory and Python Implementation is a tutorial book on reinforcement learning, with explanations of both theory and applications. Starting from a uniform mathematical framework, this book derives the theory of modern reinforcement learning in a systematic way and introduces all mainstream reinforcement learning algorithms including both classical reinforcement learning algorithms such as eligibility trace and deep reinforcement learning algorithms such as PPO, SAC, and MuZero. Every chapter is accompanied by high-quality implementations based on the latest version of Python packages such as Gym, and the implementations of deep reinforcement learning algorithms are all with both TensorFlow 2 and PyTorch 1. All codes can be found on GitHub along with their results and are runnable on a conventional laptop with either Windows, macOS, or Linux. This book is intended for readers who want to learn reinforcement learning systematically and apply reinforcement learning to practical applications. It is also ideal to academical researchers who seek theoretical foundation or algorithm enhancement in their cutting-edge AI research.

Автор: Chinnamgari Sunil Kumar
Название: R Machine Learning Projects
ISBN: 1789807948 ISBN-13(EAN): 9781789807943
Издательство: Неизвестно
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Цена: 53940.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The purpose of the book is to help a machine learning practitioner gets hands-on experience in working with real-world data and apply modern machine learning algorithms. You will learn to implement each algorithm to a specific industry problem. It covers projects involving both supervised as well as unsupervised learning approaches.

Автор: Lanham Micheal
Название: Hands-On Reinforcement Learning for Games
ISBN: 1839214937 ISBN-13(EAN): 9781839214936
Издательство: Неизвестно
Рейтинг:
Цена: 53940.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
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: Ravichandiran, Sudharsan
Название: Hands-on reinforcement learning with python -
ISBN: 1839210680 ISBN-13(EAN): 9781839210686
Издательство: Неизвестно
Рейтинг:
Цена: 60070.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
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: Michael C. Fu, Prashanth L. A.
Название: Risk-Sensitive Reinforcement Learning Via Policy Gradient Search
ISBN: 1638280266 ISBN-13(EAN): 9781638280262
Издательство: Mare Nostrum (Eurospan)
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Цена: 96090.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Reinforcement learning (RL) is one of the foundational pillars of artificial intelligence and machine learning. An important consideration in any optimization or control problem is the notion of risk, but its incorporation into RL has been a recent development. This monograph surveys research on risk-sensitive RL that uses policy gradient search.

Автор: Lanham Micheal
Название: Hands-On Deep Learning for Games
ISBN: 1788994078 ISBN-13(EAN): 9781788994071
Издательство: Неизвестно
Рейтинг:
Цена: 53940.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book will give you an in-depth view of the potential of deep learning and neural networks in game development. You will also learn to use neural nets combined with reinforcement learning for new types of game AI.