Multi-Armed Bandits: Sample Averages & the Incremental Update
This lesson is part of the course
In this lesson
You estimate the value of three app offers from 15 visits with sample averages, then rebuild the same estimate step by step with the incremental update rule and compare it with a constant step size.
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Lessons in this course
- Multi-Armed Bandits: Sample Averages & the Incremental Update Locked
- Epsilon-Greedy: Explore or Exploit, Visit by Visit Locked
- Upper Confidence Bound (UCB): Optimism with a Bonus Locked
- Returns & Discounting: G = R + γR + γ²R + … Locked
- Bellman Expectation: Evaluate a Random Policy Sweep by Sweep Locked
- Value Iteration: Take the Best Move, Sweep to Convergence Locked
- Q-Learning by Hand: Eight Updates of a Q-Table Locked
- Policy Extraction: From V* to the Best Action, and Random vs Optimal Locked