Covers: application of Reinforcement Learning

- What challenged does using RL in real world face?

Check out section 1.

Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester

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Contributors

- Objectives
- This recipe provides a high level procedure for identifying and leveraging reinforcement learning related use cases in real world.
- Potential Use Cases
- stock trading, event scheduling
- Who is This For ?
- INTERMEDIATEanyone with high level understanding of machine learning and interested in potential RL use cases in industry

Click on each of the following **annotated items** to see details.

PDF 1. Matt Taylor- RL Masterclass - Session I slides

- What is RL?
- Where can it be used?

20 minutes

PAPER 2. An empirical investigation of the challenges of real-world reinforcement learning

- What challenged does using RL in real world face?

10 minutes

CALL_TO_ACTION 3. Example RL agents learning in the browser

10 minutes

VIDEO 4. Deep RL Class Video Playlist

- How does deep reinforcement learning work?

180 minutes

OTHER 5. THE RL Book

- Where can i find everything about reinforcement learning?

15 minutes

OTHER 6. Udacity RL Class

- What is reinforcement learning?

10 minutes

ARTICLE 7. Spinning Up in Deep RL

- How can I quickly start implementing deep RL?

10 minutes

OTHER 8. Algorithms in Reinforcement Learning

- What algorithms are used in reinforcement learning?
- Why might you pick one algorithm over another?

10 minutes

ARTICLE 9. Markov Decision Process

- What is MDP?

5 minutes

ARTICLE 10. Game Theory

- What is game theory?
- How does game theory relate to RL?

5 minutes

OTHER 11. Coursera RL specialization from U Alberta

- What is reinforcement learning?
- How can I use reinforcement learning?

180 minutes

ARTICLE 12. Using Dynamic Programming to find the optimal policy in Grid World

- What is value iteration?
- What is policy iteration?

10 minutes

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