Deep Reinforcement Learning Hands-On

Table of Contents

1. What Is Reinforcement Learning?
2. OpenAI Gym API and Gymnasium
3. Deep Learning with PyTorch
4. The Cross-Entropy Method
5. Tabular Learning and the Bellman Equation
6. Deep Q-Networks
7. Higher-Level RL Libraries
8. DQN Extensions
9. Ways to Speed Up RL
10. Stocks Trading Using RL
11. Policy Gradients
12. Actor-Critic Methods - A2C and A3C
13. The TextWorld Environment
14. Web Navigation
15. Continuous Action Space
16. Trust Region Methods
17. Black-Box Optimizations in RL
18. Advanced Exploration
19. Reinforcement Learning with Human Feedback
20. AlphaGo Zero and MuZero
21. RL in Discrete Optimization
22. Multi-Agent RL