Książka Reinforcement Learning Zhiqing Xiao

Reinforcement Learning

Theory and Python Implementation

Autor: Zhiqing Xiao
Język: Angielski
Oprawa: Twarda
Wydawca: Springer, Berlin
Dostępność: Dostępna u dostawcy
Wysyłamy za 10-13 dni
331.49
Reinforcement Learning: Theory and Python Implementation is a tutorial book on reinforcement learnin...

Informacje o książce

Autor
Język
Angielski
Oprawa
Książka - Twarda
Data wydania
2023
strony
593
EAN
9789811949326
Enbook ID
39341654
Waga
977
Wymiary
155 x 235

Pełny opis

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.

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