Contact
How to shop
Delivery
Shopping guide
English
212 b
30-day return policy
Customers also purchased
/
Paperback
5 649
Ft
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.
About the book
English
Give this book today
It's easy
1 Add to cart and choose Deliver as present at the checkout 2 We'll send you a voucher 3 The book will arrive at the recipient's addressYou might also be interested in
/
Hardback
79 540
Ft
/
Paperback
4 383
Ft
/
Paperback
26 312
Ft
/
Paperback
6 619
Ft
/
Paperback
5 969
Ft
Hi! I'm Libroamiko, your book advisor.
How can I help you?