Grokking Deep Reinforcement Learning

Book Description We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment.
Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field.

Content

1. Introduction to deep reinforcement learning
2. Mathematical foundations of reinforcement learning
3. Balancing immediate and long-term goals
4. Balancing the gathering and use of information
5. Evaluating agents’ behaviors
6. Improving agents’ behaviors
7. Achieving goals more effectively and efficiently
8. Introduction to value-based deep reinforcement learning
9. More stable value-based methods
10. Sample-efficient value-based methods
11. Policy-gradient and actor-critic methods
12. Advanced actor-critic methods
13. Toward artificial general intelligence