January 2020
Intermediate to advanced
432 pages
10h 18m
English
Content preview from Hands-On Reinforcement Learning for Games
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Section 2: Exploiting the Knowledge
After exploring the basics of RL and using it in toy environments, it is time to take our agents to the next level with the addition of deep learning and several other advanced methods.
This section contains the following chapters:
- Chapter 6, Going Deep with DQN
- Chapter 7, Going Deeper with DDQN
- Chapter 8, Policy Gradient Methods
- Chapter 9, Optimizing for Continuous Control
- Chapter 10, All Together Rainbow DQN
- Chapter 11, Exploiting ML-Agents
- Chapter 12, DRL Frameworks
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.