BanditRLlib
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Lean module · Foundations

BanditRLProof.Algorithms.CUCBImpossibleCase

The source impossible-case argument with actual CUCB indices, true score gaps, finite possible-trigger sets and the source sampling constant six.

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Declarations
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Imports

BanditRLProof.Algorithms.CUCBSourceModel

Imported by

BanditRLProof, BanditRLProof.Algorithms.CUCBSufficientSampling

Declarations

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theorem BanditRLProof.CUCB.confidenceRadius_lt_half Compiled

No declaration docstring is present; use the chapter context and exact statement below.

Used in these reading views: Bandit Book

1. Finite bandits, traces, and regret

Canonical node identitydeclaration:BanditRLProof.CUCB.confidenceRadius_lt_half

Reading membership is not a proof dependency. Exact assumptions remain in the Lean statement.

theorem confidenceRadius_lt_half {m : ℕ} (Y : ℕ → Feedback m) (n : ℕ) (i : Fin m) (u : ℝ) (hu : 0<u) (hc : 6*Real.log ((n:ℝ)+1)/u^2 < (observationCount Y n i : ℝ)) : confidenceRadius Y n i (3*Real.log ((n:ℝ)+1)) < u/2
theorem BanditRLProof.CUCB.SourceModel.not_bad_of_nice_and_sufficient_observations Compiled

No declaration docstring is present; use the chapter context and exact statement below.

Used in these reading views: Bandit Book

1. Finite bandits, traces, and regret

Canonical node identitydeclaration:BanditRLProof.CUCB.SourceModel.not_bad_of_nice_and_sufficient_observations

Reading membership is not a proof dependency. Exact assumptions remain in the Lean statement.

theorem not_bad_of_nice_and_sufficient_observations (Y : ℕ → Feedback m) (n : ℕ) (a : A) (hnice : ∀i, |empiricalMean Y n i-(M.trueInput i:ℝ)|≤ confidenceRadius Y n i (3*Real.log ((n:ℝ)+1))) (horacle : S.alpha*scoreOptimum S.score (oracleInput Y n)≤S.score (oracleInput Y n) a) (hcount : ∀i∈M.possible a, 6*Real.log ((n:ℝ)+1)/(S.inverseGap a)^2 < (observationCount Y n i : ℝ)) : ¬0<S.gap a