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Reinforcement Learning

By Zhiqing Xiao

Reinforcement Learning

By Zhiqing Xiao

0 - Default Title
Description
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 systematically and introduces all mainstream reinforcement learning algorithms such as PPO, SAC, and MuZero. It also covers key technologies of GPT training such as RLHF, IRL, and PbRL. Every chapter is accompanied by high-quality implementations, and all implementations of deep reinforcement learning algorithms are with both TensorFlow and PyTorch. 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.
Product details
Binding:
Paperback
Number of Pages:
584
Release Date:
2025-09-30
Publication Date:
2025-09-30
Publisher:
Springer
Languages:
Original: English
ISBN10:
9811949352
ISBN13:
9789811949357
GPSR Manufacturer Reference:
[email protected]
Weight:
873 g
Height:
155 cm
Width:
235 cm
Thickness:
32 cm
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