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- Introductions
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Classroom Contents
An Intuition-Based Approach to Reinforcement Learning
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- 1 - Introductions
- 2 - What is the Goal
- 3 - Exploit Versus Explore
- 4 - Greedy Versus Epsilon-Greedy
- 5 - Discount Factor “g”
- 6 - Calculating Rewards
- 7 - Pseudo Code
- 8 - Working With Q-Tables 1
- 9 - Working With Q-Tables 2
- 10 - Online Q-Table
- 11 - States & Actions
- 12 - TD Learning vs Monte Carlo
- 13 - From DRA to MDP
- 14 - Stochastic Actions
- 15 - OpenAI CartPole
- 16 - More Terminology
- 17 - Useful Links
