This textbook covers principles behind main modern deep reinforcement learning algorithms that achieved breakthrough results in many domains from game AI to robotics. All required theory is explained with proofs using unified notation and emphasize on the differences between different types of algorithms and the reasons why they are constructed the way they are.
Reinforcement Learning Textbook
The textbook explains modern deep reinforcement learning algorithms, their theories, and differences, achieving breakthroughs in areas like game AI and robotics.
- Year
- 2022
- Venue
- arXiv 2022
- Authors
- 1
- Hosting
- Abstract onlyARXIV-DEFAULT
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- Abstract & full text
- arxiv.org/abs/2201.09746ARXIV-DEFAULT
- TL;DR
- Semantic Scholar