Stanford Prof Teaches Applied MDP
usamawahabkhan · x · 2026-07-13
This shares an 83-minute public video from a Stanford CS professor explaining Markov Decision Processes (MDP), focusing on how to truly master the topic.
The post notes the lecture covers:
- Search problems vs. stochastic environments
- Policy evaluation and Q-value recursive formulas
- Engineering implementations of value iteration
- Convergence bounds under cyclic graphs
The author also references an article on "distinguishing true advantage from luck," emphasizing not to mistake short-term good fortune for skill.
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