Module 2: Ray RLlib

In this module we apply the Ray RLlib software package to solve RL problems.

0Module 2 Learning Outcomes

1Intro to RLlib

2RLlib algorithm methods

3Slippery Frozen Lake

4Rendering the trained agent

5RLlib continued

6RLlib config syntax

7Saving/restoring models

8Cartpole environment

9Cartpole environment continued

10RLlib for multi-agent RL

11Multi-agent RL use cases

12What do the agents share?

13Visualizing the trained arena agent

About this course

This course teaches you the basics of reinforcement learning in an applied fashion, by leveraging the production-grade RL framework Ray RLlib. Enjoy!

About the team

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