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Add lean source and binary files (part 45)
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import Mathlib
import OAI.Combinatorics.IndependentSets.Repetition.Value
namespace OAI
noncomputable section
namespace IndependentSetsGames.Foundations.Games.FiniteDistribution
open scoped BigOperators
theorem iid_pushforward {Ω Γ : Type*} [Fintype Ω] [Fintype Γ]
(μ : FiniteDistribution Ω) (f : Ω → Γ) (n : Nat) :
(μ.pushforward f).iid n =
(μ.iid n).pushforward (fun answers i => f (answers i)) := by
classical
apply eq_of_weight_eq
intro y
simp only [iid, pushforward]
rw [Fintype.prod_sum]
apply Finset.sum_congr rfl
intro x _
by_cases h : (fun i => f (x i)) = y
· have hp : ∀ i, f (x i) = y i := congrFun h
simp [hp]
· rw [ite_eq_right h]
have hn : ¬ ∀ i, f (x i) = y i := fun hp => h (funext hp)
obtain ⟨i, hi⟩ := not_forall.mp hn
apply Finset.prod_eq_zero (Finset.mem_univ i)
simp [hi]
def uniform (Ω : Type*) [Fintype Ω] [Nonempty Ω] : FiniteDistribution Ω where
weight _ := 1 / (Fintype.card Ω : ℝ)
nonnegative _ := div_nonneg zero_le_one (Nat.cast_nonneg _)
normalized := by
have hn : (Fintype.card Ω : ℝ) ≠ 0 :=
Nat.cast_ne_zero.mpr Fintype.card_ne_zero
simp only [Finset.sum_const, Finset.card_univ, nsmul_eq_mul, one_div]
exact mul_inv_cancel₀ hn
theorem iid_uniform {Ω : Type*} [Fintype Ω] [Nonempty Ω] (n : Nat) :
(uniform Ω).iid n = uniform (Fin n → Ω) := by
classical
apply eq_of_weight_eq
intro x
simp [iid, uniform, Nat.cast_pow, one_div]
theorem expectation_uniform {Ω : Type*} [Fintype Ω] [Nonempty Ω] (f : Ω → ℝ) :
(uniform Ω).expectation f = (∑ x, f x) / (Fintype.card Ω : ℝ) := by
unfold expectation uniform
rw [← Finset.mul_sum]
simp [div_eq_mul_inv, mul_comm]
end IndependentSetsGames.Foundations.Games.FiniteDistribution
namespace IndependentSetsGames.Foundations.Games
open scoped BigOperators
namespace FiniteDistribution
variable {Ω : Type*} [Fintype Ω]
def condition (μ : FiniteDistribution Ω) (given : Ω → Bool)
(positive : 0 < μ.probability given) : FiniteDistribution Ω where
weight x := if given x then μ.weight x / μ.probability given else 0
nonnegative x := by
split
· exact div_nonneg (μ.nonnegative x) positive.le
· exact le_rfl
normalized := by
calc
_ = (∑ x, if given x then μ.weight x else 0) / μ.probability given := by
simp only [div_eq_mul_inv, Finset.sum_mul]
apply Finset.sum_congr rfl
intro x _
by_cases hx : given x = true <;> simp [hx]
_ = 1 := div_self (ne_of_gt positive)
theorem probability_condition (μ : FiniteDistribution Ω) (given event : Ω → Bool)
(positive : 0 < μ.probability given) :
(μ.condition given positive).probability event =
μ.probability (fun x => given x && event x) / μ.probability given := by
simp only [probability, condition, div_eq_mul_inv, Finset.sum_mul]
apply Finset.sum_congr rfl
intro x _
by_cases hg : given x = true <;> by_cases he : event x = true <;> simp [hg, he]
theorem probability_inter_eq_mul_conditional (μ : FiniteDistribution Ω)
(given event : Ω → Bool) (positive : 0 < μ.probability given) :
μ.probability (fun x => given x && event x) =
μ.probability given * (μ.condition given positive).probability event := by
have h := (eq_div_iff (ne_of_gt positive)).mp
(μ.probability_condition given event positive)
simpa only [mul_comm] using h.symm
theorem probability_and_le_left (μ : FiniteDistribution Ω) (event event' : Ω → Bool) :
μ.probability (fun x => event x && event' x) ≤ μ.probability event := by
apply μ.probability_mono
intro x hx
have h : event x = true ∧ event' x = true := by simpa using hx
exact h.1
theorem probability_and_le_right (μ : FiniteDistribution Ω) (event event' : Ω → Bool) :
μ.probability (fun x => event x && event' x) ≤ μ.probability event' := by
apply μ.probability_mono
intro x hx
have h : event x = true ∧ event' x = true := by simpa using hx
exact h.2
theorem probability_and_eq_zero_of_probability_eq_zero (μ : FiniteDistribution Ω)
(given event : Ω → Bool) (zero : μ.probability given = 0) :
μ.probability (fun x => given x && event x) = 0 := by
apply le_antisymm
· exact (μ.probability_and_le_left given event).trans_eq zero
· exact μ.probability_nonnegative _
@[simp] theorem probability_condition_given (μ : FiniteDistribution Ω)
(given : Ω → Bool) (positive : 0 < μ.probability given) :
(μ.condition given positive).probability given = 1 := by
rw [μ.probability_condition]
simpa only [Bool.and_self] using div_self (ne_of_gt positive)
end FiniteDistribution
namespace Game
variable {Q₁ Q₂ A₁ A₂ : Type*}
[Fintype Q₁] [Fintype Q₂] [Fintype A₁] [Fintype A₂]
{n : Nat}
theorem selectedWins_insert (G : Game Q₁ Q₂ A₁ A₂)
(strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂))
(selected : Finset (Fin n)) (coordinate : Fin n) :
G.selectedWins strategy (insert coordinate selected) =
fun questions =>
G.selectedWins strategy selected questions && G.coordinateWin strategy coordinate questions := by
classical
funext questions
apply Bool.eq_iff_iff.mpr
simp [selectedWins, and_comm]
def selectedSuccess (G : Game Q₁ Q₂ A₁ A₂)
(strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂))
(selected : Finset (Fin n)) : ℝ :=
(G.repetition n).questions.probability (G.selectedWins strategy selected)
theorem selectedSuccess_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)) : 0 ≤ G.selectedSuccess strategy selected :=
(G.repetition n).questions.probability_nonnegative _
theorem selectedSuccess_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)) : G.selectedSuccess strategy selected ≤ 1 :=
(G.repetition n).questions.probability_le_one _
@[simp] theorem selectedSuccess_empty (G : Game Q₁ Q₂ A₁ A₂)
(strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂)) :
G.selectedSuccess strategy ∅ = 1 := by
have h : G.selectedWins strategy ∅ = fun _ => true :=
funext (G.selectedWins_empty strategy)
rw [selectedSuccess, h, FiniteDistribution.probability_true]
theorem selectedSuccess_univ (G : Game Q₁ Q₂ A₁ A₂)
(strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂)) :
G.selectedSuccess strategy Finset.univ = (G.repetition n).success strategy := by
rw [selectedSuccess, G.selectedWins_univ]
rfl
theorem selectedSuccess_antitone (G : Game Q₁ Q₂ A₁ A₂)
(strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂)) :
Antitone (G.selectedSuccess strategy) := by
intro selected selected' h
exact G.selectedWins_mono strategy h
theorem selectedSuccess_insert (G : Game Q₁ Q₂ A₁ A₂)
(strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂))
(selected : Finset (Fin n)) (coordinate : Fin n)
(positive : 0 < G.selectedSuccess strategy selected) :
G.selectedSuccess strategy (insert coordinate selected) =
G.selectedSuccess strategy selected *
((G.repetition n).questions.condition (G.selectedWins strategy selected) positive).probability
(G.coordinateWin strategy coordinate) := by
unfold selectedSuccess
rw [G.selectedWins_insert]
exact (G.repetition n).questions.probability_inter_eq_mul_conditional _ _ positive
theorem selectedSuccess_insert_eq_zero (G : Game Q₁ Q₂ A₁ A₂)
(strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂))
(selected : Finset (Fin n)) (coordinate : Fin n)
(zero : G.selectedSuccess strategy selected = 0) :
G.selectedSuccess strategy (insert coordinate selected) = 0 := by
apply le_antisymm
· exact (G.selectedSuccess_antitone strategy (Finset.subset_insert coordinate selected)).trans_eq zero
· exact G.selectedSuccess_nonnegative _ _
end Game
end IndependentSetsGames.Foundations.Games
end
end OAI