BanditRLlib
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Lean module · Tsallis-FTRL

BanditRLProof.TsallisFTRLMinimizerUniqueness

The square-root sum is strictly concave on a nonempty standard simplex, so the half-Tsallis regularized objective is strictly convex there. The project-level finite simplex leaves coordinates outside arms unconstrained; accordingly, the public uniqueness theorem identifies exactly the supported coordinates.

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Imports

BanditRLProof.TsallisFTRLMinimizerExistence

Imported by

BanditRLProof, BanditRLProof.TsallisFTRLMinimizerMeasurability

Declarations

Open an item to read its exact compact statement and source link. Detailed teaching notes are linked when registered.

theorem BanditRLProof.Tsallis.strictConcaveOn_sum_sqrt_stdSimplex Compiled

The finite sum of square roots is strictly concave on every nonempty standard simplex.

Used in these reading views: Bandit Book · Online Learning Book

8. Tsallis-FTRL, corruption, and nonstationarity

Canonical node identitydeclaration:BanditRLProof.Tsallis.strictConcaveOn_sum_sqrt_stdSimplex

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

theorem strictConcaveOn_sum_sqrt_stdSimplex {Action : Type u} [Fintype Action] [Nonempty Action] : StrictConcaveOn Real (stdSimplex Real Action) (fun p : Action -> Real => (Finset.univ : Finset Action).sum (fun action => Real.sqrt (p action)))
theorem BanditRLProof.Tsallis.strictConvexOn_regularizedObjective_half_stdSimplex Compiled

On a nonempty finite standard simplex, the half-Tsallis regularized objective is strictly convex in the probability vector.

Used in these reading views: Bandit Book · Online Learning Book

8. Tsallis-FTRL, corruption, and nonstationarity

Canonical node identitydeclaration:BanditRLProof.Tsallis.strictConvexOn_regularizedObjective_half_stdSimplex

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

theorem strictConvexOn_regularizedObjective_half_stdSimplex {Action : Type u} [Fintype Action] [Nonempty Action] (eta : Real) (score : Action -> Real) : StrictConvexOn Real (stdSimplex Real Action) (fun p => FTRL.regularizedObjective Finset.univ eta (negEntropyRegularizer Finset.univ (1 / 2 : Real)) score p)
theorem BanditRLProof.Tsallis.isRegularizedMinimizer_half_eq_on_arms Compiled

Two half-Tsallis minimizers have identical coordinates on the explicit arm set. Coordinates outside `arms` are intentionally not constrained by the project finite-simplex predicate or objective.

Used in these reading views: Bandit Book · Online Learning Book

8. Tsallis-FTRL, corruption, and nonstationarity

Canonical node identitydeclaration:BanditRLProof.Tsallis.isRegularizedMinimizer_half_eq_on_arms

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

theorem isRegularizedMinimizer_half_eq_on_arms {Action : Type u} [DecidableEq Action] (arms : Finset Action) (harms : arms.Nonempty) (eta : Real) (score p q : Action -> Real) (hp : FTRL.IsRegularizedMinimizer (FTRL.finiteSimplex arms) arms eta (negEntropyRegularizer arms (1 / 2 : Real)) score p) (hq : FTRL.IsRegularizedMinimizer (FTRL.finiteSimplex arms) arms eta (negEntropyRegularizer arms (1 / 2 : Real)) score q) : forall action, action ∈ arms -> p action = q action
theorem BanditRLProof.Tsallis.halfTsallisMinimizer_eq_on_arms Compiled

The canonical selected minimizer agrees on every supported coordinate with any other half-Tsallis minimizer certificate.

Used in these reading views: Bandit Book · Online Learning Book

8. Tsallis-FTRL, corruption, and nonstationarity

Canonical node identitydeclaration:BanditRLProof.Tsallis.halfTsallisMinimizer_eq_on_arms

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

theorem halfTsallisMinimizer_eq_on_arms {Action : Type u} [DecidableEq Action] (arms : Finset Action) (harms : arms.Nonempty) (eta : Real) (score p : Action -> Real) (hp : FTRL.IsRegularizedMinimizer (FTRL.finiteSimplex arms) arms eta (negEntropyRegularizer arms (1 / 2 : Real)) score p) : forall action, action ∈ arms -> halfTsallisMinimizer arms harms eta score action = p action