Theoremadvanced
Convergence of tabular Q-learning
Also called Watkins-Dayan theorem.
Tabular Q-learning converges to the optimal Q-function under visitation and step-size conditions.
Tabular Q-learning converges to the optimal Q-function under visitation and step-size conditions.
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The build computes these levels from the evidence in the repository. Each row says what the next level needs. Read what the levels mean.
| Ladder | Level | What the next level needs |
|---|---|---|
| Human proof | H0 no proof |
|
| Lean | L0 no Lean part |
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| Visual | V0 none |
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| Writing | W0 stub |
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