import Mathlib import OAI.Combinatorics.IndependentSets.Repetition.TotalVariation import OAI.Combinatorics.IndependentSets.Repetition.Pinsker namespace OAI namespace IndependentSetsGames.Foundations.Repetition open scoped BigOperators open Games Information noncomputable section variable {Q₁ Q₂ A₁ A₂ : Type*} [Fintype Q₁] [Fintype Q₂] [Fintype A₁] [Fintype A₂] [DecidableEq Q₁] [DecidableEq Q₂] {n : Nat} def selectedTupleLikelihood (G : Game Q₁ Q₂ A₁ A₂) (strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂)) (selected : Finset (Fin n)) (questions : Fin n → Q₁ × Q₂) : ℝ := if G.selectedWins strategy selected (Game.tupleQuestionEquiv n questions) then 1 else 0 omit [DecidableEq Q₁] [DecidableEq Q₂] in theorem selectedTupleLikelihood_nonnegative (G : Game Q₁ Q₂ A₁ A₂) (strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂)) (selected : Finset (Fin n)) (questions : Fin n → Q₁ × Q₂) : 0 ≤ selectedTupleLikelihood G strategy selected questions := by unfold selectedTupleLikelihood split <;> norm_num omit [DecidableEq Q₁] [DecidableEq Q₂] in theorem selectedTupleLikelihood_le_one (G : Game Q₁ Q₂ A₁ A₂) (strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂)) (selected : Finset (Fin n)) (questions : Fin n → Q₁ × Q₂) : selectedTupleLikelihood G strategy selected questions ≤ 1 := by unfold selectedTupleLikelihood split <;> norm_num omit [DecidableEq Q₁] [DecidableEq Q₂] in theorem selectedTupleLikelihood_mass (G : Game Q₁ Q₂ A₁ A₂) (strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂)) (selected : Finset (Fin n)) : (∑ questions, independentProduct (fun _ : Fin n => G.questions.weight) questions * selectedTupleLikelihood G strategy selected questions) = G.selectedSuccess strategy selected := by classical change _ = ((G.questions.iid n).transport (Game.tupleQuestionEquiv n)).probability (G.selectedWins strategy selected) rw [FiniteDistribution.probability_transport] simp only [FiniteDistribution.probability, FiniteDistribution.iid, independentProduct, selectedTupleLikelihood, mul_ite, mul_one, mul_zero] def selectedQuestionMarginal (G : Game Q₁ Q₂ A₁ A₂) (strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂)) (selected : Finset (Fin n)) (positive : 0 < G.selectedSuccess strategy selected) (i : Fin n) : FiniteDistribution (Q₁ × Q₂) := ((G.repetition n).questions.condition (G.selectedWins strategy selected) positive).pushforward (fun questions => (questions.1 i, questions.2 i)) theorem selectedQuestionMarginal_weight (G : Game Q₁ Q₂ A₁ A₂) (strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂)) (selected : Finset (Fin n)) (positive : 0 < G.selectedSuccess strategy selected) (i : Fin n) : (selectedQuestionMarginal G strategy selected positive i).weight = coordinateMarginal (posterior (independentProduct (fun _ : Fin n => G.questions.weight)) (selectedTupleLikelihood G strategy selected) (G.selectedSuccess strategy selected)) i := by classical funext a simp only [selectedQuestionMarginal, FiniteDistribution.pushforward, FiniteDistribution.condition, coordinateMarginal] refine Fintype.sum_equiv (Game.tupleQuestionEquiv (Q₁ := Q₁) (Q₂ := Q₂) n).symm _ _ ?_ intro questions cases he : G.selectedWins strategy selected questions <;> simp [Game.repetition_question_weight, Game.tupleQuestionEquiv, posterior, independentProduct, selectedTupleLikelihood, Game.selectedSuccess, he] theorem selectedQuestionMarginal_totalVariation_sq_sum_le_log (G : Game Q₁ Q₂ A₁ A₂) (strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂)) (selected : Finset (Fin n)) (positive : 0 < G.selectedSuccess strategy selected) : (∑ i : Fin n, (selectedQuestionMarginal G strategy selected positive i).totalVariation G.questions ^ 2) ≤ Real.log (1 / G.selectedSuccess strategy selected) := by classical change (∑ i : Fin n, Information.totalVariation (selectedQuestionMarginal G strategy selected positive i).weight G.questions.weight ^ 2) ≤ _ simp_rw [selectedQuestionMarginal_weight] exact posterior_coordinate_totalVariation_sq_sum_le_log (fun _ : Fin n => G.questions.weight) (fun _ => gameLaw_isProbability G.questions) (selectedTupleLikelihood G strategy selected) (selectedTupleLikelihood_nonnegative G strategy selected) (selectedTupleLikelihood_le_one G strategy selected) positive (selectedTupleLikelihood_mass G strategy selected) theorem unselectedQuestionMarginal_totalVariation_sq_sum_le_log (G : Game Q₁ Q₂ A₁ A₂) (strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂)) (selected : Finset (Fin n)) (positive : 0 < G.selectedSuccess strategy selected) : (∑ i : {i : Fin n // i ∉ selected}, (selectedQuestionMarginal G strategy selected positive i.1).totalVariation G.questions ^ 2) ≤ Real.log (1 / G.selectedSuccess strategy selected) := by classical let d : Fin n → ℝ := fun i => (selectedQuestionMarginal G strategy selected positive i).totalVariation G.questions have hfull := selectedQuestionMarginal_totalVariation_sq_sum_le_log G strategy selected positive have hsplit := Fintype.sum_subtype_add_sum_subtype (fun i : Fin n => i ∈ selected) (fun i => d i ^ 2) have hinst : Subtype.fintype (fun i : Fin n => i ∈ selected) = Finset.Subtype.fintype selected := Subsingleton.elim _ _ rw [hinst] at hsplit have hselected : 0 ≤ ∑ i : {i : Fin n // i ∈ selected}, d i.1 ^ 2 := Finset.sum_nonneg (fun _ _ => sq_nonneg _) change (∑ i : {i : Fin n // i ∉ selected}, d i.1 ^ 2) ≤ _ change (∑ i : Fin n, d i ^ 2) ≤ _ at hfull linarith theorem unselectedQuestionMarginal_totalVariation_sum_le_sqrt (G : Game Q₁ Q₂ A₁ A₂) (strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂)) (selected : Finset (Fin n)) (positive : 0 < G.selectedSuccess strategy selected) : (∑ i : {i : Fin n // i ∉ selected}, (selectedQuestionMarginal G strategy selected positive i.1).totalVariation G.questions) ≤ Real.sqrt ((Fintype.card {i : Fin n // i ∉ selected} : ℝ) * Real.log (1 / G.selectedSuccess strategy selected)) := by classical let d : {i : Fin n // i ∉ selected} → ℝ := fun i => (selectedQuestionMarginal G strategy selected positive i.1).totalVariation G.questions have hsq := unselectedQuestionMarginal_totalVariation_sq_sum_le_log G strategy selected positive have hcs := Finset.sum_mul_sq_le_sq_mul_sq (Finset.univ : Finset {i : Fin n // i ∉ selected}) d (fun _ => (1 : ℝ)) simp only [mul_one, one_pow, Finset.sum_const, Finset.card_univ, nsmul_eq_mul, mul_one] at hcs have hln : 0 ≤ Real.log (1 / G.selectedSuccess strategy selected) := (Finset.sum_nonneg (fun _ _ => sq_nonneg _)).trans hsq have hcard : 0 ≤ (Fintype.card {i : Fin n // i ∉ selected} : ℝ) := Nat.cast_nonneg _ have hmul := mul_le_mul_of_nonneg_left hsq hcard have hsqrt := Real.sq_sqrt (mul_nonneg hcard hln) have hsqrtpos := Real.sqrt_nonneg ((Fintype.card {i : Fin n // i ∉ selected} : ℝ) * Real.log (1 / G.selectedSuccess strategy selected)) change (∑ i, d i) ≤ _ change (∑ i, d i ^ 2) ≤ _ at hsq change (Fintype.card {i : Fin n // i ∉ selected} : ℝ) * (∑ i, d i ^ 2) ≤ _ at hmul nlinarith theorem unselectedQuestionMarginal_totalVariation_sum_le_sqrt_sub_card (G : Game Q₁ Q₂ A₁ A₂) (strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂)) (selected : Finset (Fin n)) (positive : 0 < G.selectedSuccess strategy selected) : (∑ i : {i : Fin n // i ∉ selected}, (selectedQuestionMarginal G strategy selected positive i.1).totalVariation G.questions) ≤ Real.sqrt (((n - selected.card : Nat) : ℝ) * Real.log (1 / G.selectedSuccess strategy selected)) := by classical have hcard : Fintype.card {i : Fin n // i ∉ selected} = n - selected.card := by simp simpa only [hcard] using unselectedQuestionMarginal_totalVariation_sum_le_sqrt G strategy selected positive end end IndependentSetsGames.Foundations.Repetition end OAI