Book Content
chapters • 18h12m total length
1. What is Reinforcement Learning?
2. OpenAI Gym
3. Deep Learning with PyTorch
4. The Cross-Entropy Method
5. Tabular Learning and the Bellman Equation
6. Deep Q-Networks
7. DQN Extensions
8. Stocks Trading Using RL
9. Policy Gradients – An Alternative
10. The Actor-Critic Method
11. Asynchronous Advantage Actor-Critic
12. Chatbots Training with RL
13. Web Navigation
14. Continuous Action Space
15. Trust Regions – TRPO, PPO, and ACKTR
16. Black-Box Optimization in RL
17. Beyond Model-Free – Imagination
18. AlphaGo Zero
