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Part four of a six part series on Reinforcement Learning. As the title says, it covers Temporal Difference Learning, Sarsa and Q-Learning, along with some examples.
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SOURCES
[1] R. Sutton and A. Barto. Reinforcement learning: An Introduction (2nd Ed). MIT Press, 2018.
[2] H. Hasselt, et al. RL Lecture Series, Deepmind and UCL, 2021, • DeepMind x UCL | Deep Learning Lectur...
SOURCE NOTES
The video covers topics from chapters 6 and 7 from [1]. The whole series teaches from [1]. [2] has been a useful secondary resource.
TIMESTAMP
0:00 What We'll Learn
0:52 No Review
1:18 TD as an Adjusted Version of MC
2:49 TD Visualized with a Markov Reward Process
6:34 N-Step Temporal Difference Learning
8:08 MC vs TD on an Evaluation Example
11:50 TD's Trade-Off between N and Alpha
12:47 Why does TD Perform Better than MC?
15:29 N-Step Sarsa
17:15 Why have N above 1?
19:02 Q-Learning
20:50 Expected Sarsa
21:48 Cliff Walking
25:04 Windy GridWorld
28:12 Watch the Next Video!
NOTES
Code to compare TD vs MC on the evaluation task: https://github.com/Duane321/mutual_in...
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