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Add lean source and binary files (part 62)
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import Mathlib
import OAI.Computability.MinUncut.Estimates.FaceUpdateSelf
import OAI.Computability.MinUncut.Games.AffineLabels
import OAI.Computability.MinUncut.Machines.OuterAlphabets
namespace OAI
noncomputable section
open scoped BigOperators
namespace MinUncut.Outer
open MinUncut.Inner
attribute [local instance] Classical.propDecidable
variable {Name I : Type*}
abbrev SecondQuestion (Name : Type*) := Name ⊕ Equation Name
def secondSlotCount : SecondQuestion Name → ℕ
| .inl _ => 1
| .inr _ => 3
abbrev secondSlot (v : SecondQuestion Name) := Fin (secondSlotCount v) → F₂
abbrev FirstAlphabet (U : I → Equation Name) := ∀ j, alphabet (U j)
abbrev FirstDirection (U : I → Equation Name) := ∀ j, (alphabet (U j)).direction
abbrev SecondAlphabet (V : I → SecondQuestion Name) := ∀ j, secondSlot (V j)
def slotQuestion (E : Equation Name) (hidden : Bool) (p : Fin 3) : SecondQuestion Name :=
if hidden then .inl (E.names p) else .inr E
def slotProjection (E : Equation Name) (hidden : Bool) (p : Fin 3) :
alphabet E →ᵃ[F₂] secondSlot (slotQuestion E hidden p) := by
cases hidden
· exact (alphabet E).subtype
· exact (LinearMap.pi (fun _ : Fin 1 => (LinearMap.proj p : Triple →ₗ[F₂] F₂))).toAffineMap.comp (alphabet E).subtype
def secondQuestion (U : I → Equation Name) (hidden : I → Bool) (position : I → Fin 3) :
I → SecondQuestion Name := fun j => slotQuestion (U j) (hidden j) (position j)
def projection (U : I → Equation Name) (hidden : I → Bool) (position : I → Fin 3) :
FirstAlphabet U →ᵃ[F₂] SecondAlphabet (secondQuestion U hidden position) :=
AffineMap.pi (fun j => (slotProjection (U j) (hidden j) (position j)).comp (AffineMap.proj j))
@[simp] lemma projection_apply (U : I → Equation Name) (hidden : I → Bool)
(position : I → Fin 3) (a : FirstAlphabet U) (j : I) :
projection U hidden position a j=slotProjection (U j) (hidden j) (position j) (a j) := rfl
def evaluatedTriple (s : Name → F₂) (E : Equation Name) : Triple := fun p => s (E.names p)
def Satisfied (s : Name → F₂) (E : Equation Name) : Prop := parity (evaluatedTriple s E)=E.rhs
lemma evaluatedTriple_valid (s : Name → F₂) (E : Equation Name) (h : Satisfied s E) :
Valid E (evaluatedTriple s E) :=
⟨h,fun _ _ he => congrArg s he⟩
def firstLabel (s : Name → F₂) (U : I → Equation Name) : FirstAlphabet U :=
fun j => if h : Satisfied s (U j) then ⟨evaluatedTriple s (U j),evaluatedTriple_valid s (U j) h⟩
else origin (U j)
def secondSlotLabel (s : Name → F₂) : (v : SecondQuestion Name) → secondSlot v
| .inl x => fun _ => s x
| .inr E => evaluatedTriple s E
def secondLabel (s : Name → F₂) (V : I → SecondQuestion Name) : SecondAlphabet V :=
fun j => secondSlotLabel s (V j)
lemma honest_slot (s : Name → F₂) (E : Equation Name) (h : Satisfied s E)
(hidden : Bool) (p : Fin 3) :
slotProjection E hidden p ⟨evaluatedTriple s E,evaluatedTriple_valid s E h⟩ =
secondSlotLabel s (slotQuestion E hidden p) := by
cases hidden <;> rfl
lemma honest_projection (s : Name → F₂) (U : I → Equation Name)
(h : ∀ j, Satisfied s (U j)) (hidden : I → Bool) (position : I → Fin 3) :
projection U hidden position (firstLabel s U) =
secondLabel s (secondQuestion U hidden position) := by
funext j
change slotProjection (U j) (hidden j) (position j) (firstLabel s U j)=_
simp only [firstLabel,dite_eq_left (h j)]
exact honest_slot s (U j) (h j) (hidden j) (position j)
open MinUncut.Inner
attribute [local instance] Classical.propDecidable
variable {Name I : Type*} [Fintype I]
def slotFunctional (v : SecondQuestion Name) (β : F₂) (l : Module.Dual F₂ Triple) :
Module.Dual F₂ (secondSlot v) := by
cases v with
| inl x => exact β • (LinearMap.proj (0 : Fin 1))
| inr E => exact l
lemma slotFunctional_add (v : SecondQuestion Name) (β γ : F₂) (l k : Module.Dual F₂ Triple) :
slotFunctional v (β+γ) (l+k)=slotFunctional v β l + slotFunctional v γ k := by
cases v with
| inl x => exact add_smul _ _ _
| inr E => rfl
lemma slotFunctional_smul (v : SecondQuestion Name) (c β : F₂) (l : Module.Dual F₂ Triple) :
slotFunctional v (c • β) (c • l)=c • slotFunctional v β l := by
cases v with
| inl x =>
change (c*β) • (LinearMap.proj (0 : Fin 1) : Module.Dual F₂ (Fin 1 → F₂)) = _
exact mul_smul _ _ _
| inr E => rfl
def directLinear (V : I → SecondQuestion Name) (β : I → F₂)
(l : I → Module.Dual F₂ Triple) : Module.Dual F₂ (SecondAlphabet V) :=
∑ j, (slotFunctional (V j) (β j) (l j)).comp (LinearMap.proj j)
def directHint (V : I → SecondQuestion Name) (κ : F₂) (β : I → F₂)
(l : I → Module.Dual F₂ Triple) : Forms (SecondAlphabet V) :=
(directLinear V β l).toAffineMap + AffineMap.const F₂ _ κ
@[simp] lemma directHint_apply (V : I → SecondQuestion Name) (κ : F₂) (β : I → F₂)
(l : I → Module.Dual F₂ Triple) (a : SecondAlphabet V) :
directHint V κ β l a = (∑ j, slotFunctional (V j) (β j) (l j) (a j))+κ := by
simp [directHint,directLinear]
lemma slotFunctional_project (E : Equation Name) (hidden : Bool) (p : Fin 3)
(β : F₂) (l : Module.Dual F₂ Triple) (a : alphabet E) :
slotFunctional (slotQuestion E hidden p) β l (slotProjection E hidden p a) =
if hidden then β*a.val p else l a.val := by
cases hidden <;> rfl
lemma pulledHint_apply (U : I → Equation Name) (hidden : I → Bool) (pos : I → Fin 3)
(κ : F₂) (β : I → F₂) (l : I → Module.Dual F₂ Triple) (a : FirstAlphabet U) :
formPullback (projection U hidden pos)
(directHint (secondQuestion U hidden pos) κ β l) a =
(∑ j, if hidden j then β j*(a j).val (pos j) else l j (a j).val)+κ := by
change directHint (secondQuestion U hidden pos) κ β l (projection U hidden pos a)=_
rw [directHint_apply]
congr 1
apply Finset.sum_congr rfl
intro j _
exact slotFunctional_project (U j) (hidden j) (pos j) (β j) (l j) (a j)
lemma pulledHint_independent_active (U : I → Equation Name) (hidden : I → Bool)
(pos pos' : I → Fin 3) (κ : F₂) (β : I → F₂) (l : I → Module.Dual F₂ Triple)
(h : ∀ j, hidden j=true → pos j≠pos' j → β j=0) :
formPullback (projection U hidden pos)
(directHint (secondQuestion U hidden pos) κ β l) =
formPullback (projection U hidden pos')
(directHint (secondQuestion U hidden pos') κ β l) := by
ext a
rw [pulledHint_apply,pulledHint_apply]
congr 1
apply Finset.sum_congr rfl
intro j _
by_cases hh : hidden j=true
· simp only [hh,↓reduceIte]
by_cases hp : pos j=pos' j
· rw [hp]
· rw [h j hh hp]; simp
· simp [hh]
def hintGenerator (V : I → SecondQuestion Name) :
(F₂ × ((I → F₂) × (I → Module.Dual F₂ Triple))) →ₗ[F₂] Forms (SecondAlphabet V) where
toFun c := directHint V c.1 c.2.1 c.2.2
map_add' c d := by
ext a
change directHint V (c.1+d.1) (c.2.1+d.2.1) (c.2.2+d.2.2) a =
directHint V c.1 c.2.1 c.2.2 a + directHint V d.1 d.2.1 d.2.2 a
simp only [directHint_apply,Pi.add_apply,slotFunctional_add,LinearMap.add_apply,
Finset.sum_add_distrib]
abel
map_smul' k c := by
ext a
change directHint V (k • c.1) (k • c.2.1) (k • c.2.2) a =
k • (directHint V c.1 c.2.1 c.2.2 a)
simp only [directHint_apply,Pi.smul_apply,slotFunctional_smul,LinearMap.smul_apply,
← Finset.smul_sum,← smul_add]
def unpackFunctional : (v : SecondQuestion Name) → Module.Dual F₂ (secondSlot v) →
F₂ × Module.Dual F₂ Triple
| .inl _, l => (l (fun _ => 1),0)
| .inr _, l => (0,l)
lemma oneSlotDual (l : Module.Dual F₂ (Fin 1 → F₂)) :
l (fun _ => 1) • (LinearMap.proj (0 : Fin 1)) = l := by
apply LinearMap.ext
intro a
have ha : a=a 0 • (fun _ : Fin 1 => (1 : F₂)) := by
funext p
fin_cases p
simp
change l (fun _ => 1)*a 0=l a
calc
_ = a 0 • l (fun _ => 1) := mul_comm _ _
_ = l (a 0 • (fun _ => 1)) := (l.map_smul _ _).symm
_ = l a := congrArg l ha.symm
lemma slotFunctional_unpack (v : SecondQuestion Name)
(l : Module.Dual F₂ (secondSlot v)) :
slotFunctional v (unpackFunctional v l).1 (unpackFunctional v l).2=l := by
cases v with
| inl x => exact oneSlotDual l
| inr E => rfl
lemma hintGenerator_surjective (V : I → SecondQuestion Name) :
Function.Surjective (hintGenerator V) := by
classical
intro f
let localPart (j : I) : Module.Dual F₂ (secondSlot (V j)) :=
f.linear.comp (LinearMap.single F₂ (fun j => secondSlot (V j)) j)
let c := fun j => unpackFunctional (V j) (localPart j)
refine ⟨(f 0,(fun j => (c j).1,fun j => (c j).2)),?_⟩
ext a
change directHint V (f 0) (fun j => (c j).1) (fun j => (c j).2) a=f a
rw [directHint_apply]
have hlin : (∑ j,slotFunctional (V j) (c j).1 (c j).2 (a j))=f.linear a := by
simp only [c,slotFunctional_unpack,localPart,LinearMap.comp_apply,LinearMap.single_apply]
rw [← map_sum,Finset.univ_sum_single]
rw [hlin]
simpa using (f.map_vadd (0 : SecondAlphabet V) a).symm
attribute [local instance] BinaryFourier.dualFintype
lemma uniform_hintGenerator (V : I → SecondQuestion Name) (f : Forms (SecondAlphabet V) → ℝ) :
(𝔼 c, f (hintGenerator V c)) = 𝔼 L, f L :=
IndependentSquares.expect_surjective_linear (hintGenerator V) (hintGenerator_surjective V) f
def hintTupleGenerator (V : I → SecondQuestion Name) (q : ℕ) :
(Fin q → (F₂ × ((I → F₂) × (I → Module.Dual F₂ Triple)))) →ₗ[F₂]
(Fin q → Forms (SecondAlphabet V)) :=
LinearMap.pi (fun k => (hintGenerator V).comp (LinearMap.proj k))
lemma hintTupleGenerator_surjective (V : I → SecondQuestion Name) (q : ℕ) :
Function.Surjective (hintTupleGenerator V q) := by
intro f
choose c hc using fun k => hintGenerator_surjective V (f k)
exact ⟨c,funext hc⟩
lemma uniform_hintTupleGenerator (V : I → SecondQuestion Name) (q : ℕ)
(f : (Fin q → Forms (SecondAlphabet V)) → ℝ) :
(𝔼 c, f (hintTupleGenerator V q c)) = 𝔼 L, f L :=
IndependentSquares.expect_surjective_linear (hintTupleGenerator V q)
(hintTupleGenerator_surjective V q) f
end MinUncut.Outer
end
namespace MinUncutGames.Foundations.Games
open scoped BigOperators
noncomputable section
structure FiniteDistribution (Ω : Type*) [Fintype Ω] where
weight : Ω → ℝ
nonnegative : ∀ x, 0 ≤ weight x
normalized : ∑ x, weight x = 1
namespace FiniteDistribution
variable {Ω Γ : Type*} [Fintype Ω] [Fintype Γ]
def expectation (μ : FiniteDistribution Ω) (f : Ω → ℝ) : ℝ :=
∑ x, μ.weight x * f x
def probability (μ : FiniteDistribution Ω) (event : Ω → Bool) : ℝ :=
∑ x, if event x then μ.weight x else 0
theorem probability_nonnegative (μ : FiniteDistribution Ω) (event : Ω → Bool) :
0 ≤ μ.probability event := by
apply Finset.sum_nonneg
intro x _
split
· exact μ.nonnegative x
· exact le_rfl
theorem probability_le_one (μ : FiniteDistribution Ω) (event : Ω → Bool) :
μ.probability event ≤ 1 := by
rw [← μ.normalized]
apply Finset.sum_le_sum
intro x _
split
· exact le_rfl
· exact μ.nonnegative x
@[simp] theorem probability_true (μ : FiniteDistribution Ω) :
μ.probability (fun _ => true) = 1 := by
simpa [probability] using μ.normalized
@[simp] theorem probability_false (μ : FiniteDistribution Ω) :
μ.probability (fun _ => false) = 0 := by
simp [probability]
theorem probability_mono (μ : FiniteDistribution Ω) {event event' : Ω → Bool}
(h : ∀ x, event x = true → event' x = true) :
μ.probability event ≤ μ.probability event' := by
apply Finset.sum_le_sum
intro x _
by_cases hx : event x = true
· simp [hx, h x hx]
· simp [hx]
split
· exact μ.nonnegative x
· exact le_rfl
def pushforward (μ : FiniteDistribution Ω) (f : Ω → Γ) : FiniteDistribution Γ := by
classical
exact
{ weight := fun y => ∑ x, if f x = y then μ.weight x else 0
nonnegative := fun y => Finset.sum_nonneg fun x _ => by
split
· exact μ.nonnegative x
· exact le_rfl
normalized := by
rw [Finset.sum_comm]
simpa using μ.normalized }
theorem probability_pushforward (μ : FiniteDistribution Ω) (f : Ω → Γ)
(event : Γ → Bool) :
(μ.pushforward f).probability event = μ.probability (fun x => event (f x)) := by
classical
simp only [probability, pushforward]
calc
_ = ∑ y, ∑ x, if f x = y then (if event y then μ.weight x else 0) else 0 := by
apply Finset.sum_congr rfl
intro y _
by_cases hy : event y = true <;> simp [hy]
_ = _ := by rw [Finset.sum_comm]; simp
def transport (μ : FiniteDistribution Ω) (equiv : Ω ≃ Γ) : FiniteDistribution Γ where
weight y := μ.weight (equiv.symm y)
nonnegative y := μ.nonnegative (equiv.symm y)
normalized := by rw [equiv.symm.sum_comp, μ.normalized]
theorem probability_transport (μ : FiniteDistribution Ω) (equiv : Ω ≃ Γ)
(event : Γ → Bool) :
(μ.transport equiv).probability event = μ.probability (fun x => event (equiv x)) := by
unfold probability transport
exact Fintype.sum_equiv equiv.symm _ _ (fun _ => by simp)
def iid (μ : FiniteDistribution Ω) (n : Nat) : FiniteDistribution (Fin n → Ω) where
weight x := ∏ i, μ.weight (x i)
nonnegative x := Finset.prod_nonneg fun i _ => μ.nonnegative (x i)
normalized := by rw [← Fintype.sum_pow, μ.normalized, one_pow]
theorem probability_iid_all (μ : FiniteDistribution Ω) (event : Ω → Bool) (n : Nat) :
(μ.iid n).probability (fun x => decide (∀ i, event (x i) = true)) =
μ.probability event ^ n := by
classical
unfold probability iid
rw [Fintype.sum_pow]
apply Finset.sum_congr rfl
intro x _
simp only [decide_eq_true_eq]
by_cases h : ∀ i, event (x i) = true
· simp [h]
· rw [ite_eq_right h]
obtain ⟨i, hi⟩ := not_forall.mp h
symm
apply Finset.prod_eq_zero (Finset.mem_univ i)
simp [hi]
end FiniteDistribution
abbrev Strategy (Q₁ Q₂ A₁ A₂ : Type*) := (Q₁ → A₁) × (Q₂ → A₂)
structure Game (Q₁ Q₂ A₁ A₂ : Type*) [Fintype Q₁] [Fintype Q₂]
[Fintype A₁] [Fintype A₂] where
questions : FiniteDistribution (Q₁ × Q₂)
accepts : Q₁ → Q₂ → A₁ → A₂ → Bool
namespace Game
variable {Q₁ Q₂ A₁ A₂ : Type*}
[Fintype Q₁] [Fintype Q₂] [Fintype A₁] [Fintype A₂]
def wins (G : Game Q₁ Q₂ A₁ A₂) (strategy : Strategy Q₁ Q₂ A₁ A₂)
(questions : Q₁ × Q₂) : Bool :=
G.accepts questions.1 questions.2 (strategy.1 questions.1) (strategy.2 questions.2)
def success (G : Game Q₁ Q₂ A₁ A₂) (strategy : Strategy Q₁ Q₂ A₁ A₂) : ℝ :=
G.questions.probability (G.wins strategy)
theorem success_nonnegative (G : Game Q₁ Q₂ A₁ A₂)
(strategy : Strategy Q₁ Q₂ A₁ A₂) : 0 ≤ G.success strategy :=
G.questions.probability_nonnegative _
theorem success_le_one (G : Game Q₁ Q₂ A₁ A₂)
(strategy : Strategy Q₁ Q₂ A₁ A₂) : G.success strategy ≤ 1 :=
G.questions.probability_le_one _
def simulatedStrategy {R₁ R₂ B₁ B₂ : Type*}
(questionMap₁ : Q₁ → R₁) (questionMap₂ : Q₂ → R₂)
(answerMap₁ : Q₁ → B₁ → A₁) (answerMap₂ : Q₂ → B₂ → A₂)
(strategy : Strategy R₁ R₂ B₁ B₂) : Strategy Q₁ Q₂ A₁ A₂ :=
(fun x => answerMap₁ x (strategy.1 (questionMap₁ x)),
fun y => answerMap₂ y (strategy.2 (questionMap₂ y)))
theorem success_le_of_localSimulation {R₁ R₂ B₁ B₂ : Type*}
[Fintype R₁] [Fintype R₂] [Fintype B₁] [Fintype B₂]
(G : Game Q₁ Q₂ A₁ A₂) (H : Game R₁ R₂ B₁ B₂)
(questionMap₁ : Q₁ → R₁) (questionMap₂ : Q₂ → R₂)
(answerMap₁ : Q₁ → B₁ → A₁) (answerMap₂ : Q₂ → B₂ → A₂)
(questionLaw : H.questions =
G.questions.pushforward (fun q => (questionMap₁ q.1, questionMap₂ q.2)))
(acceptance : ∀ x y a b,
H.accepts (questionMap₁ x) (questionMap₂ y) a b = true →
G.accepts x y (answerMap₁ x a) (answerMap₂ y b) = true)
(strategy : Strategy R₁ R₂ B₁ B₂) :
H.success strategy ≤
G.success (simulatedStrategy questionMap₁ questionMap₂ answerMap₁ answerMap₂ strategy) := by
unfold success
rw [questionLaw, FiniteDistribution.probability_pushforward]
apply FiniteDistribution.probability_mono
intro questions h
exact acceptance questions.1 questions.2 _ _ h
def tupleQuestionEquiv (n : Nat) :
(Fin n → Q₁ × Q₂) ≃ (Fin n → Q₁) × (Fin n → Q₂) where
toFun questions := (fun i => (questions i).1, fun i => (questions i).2)
invFun questions := fun i => (questions.1 i, questions.2 i)
left_inv _ := rfl
right_inv _ := rfl
def repetition (G : Game Q₁ Q₂ A₁ A₂) (n : Nat) :
Game (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂) := by
classical
exact
{ questions := (G.questions.iid n).transport (tupleQuestionEquiv n)
accepts := fun x y a b => decide (∀ i, G.accepts (x i) (y i) (a i) (b i) = true) }
def repeatStrategy (strategy : Strategy Q₁ Q₂ A₁ A₂) (n : Nat) :
Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂) :=
(fun x i => strategy.1 (x i), fun y i => strategy.2 (y i))
theorem success_repeatStrategy (G : Game Q₁ Q₂ A₁ A₂)
(strategy : Strategy Q₁ Q₂ A₁ A₂) (n : Nat) :
(G.repetition n).success (repeatStrategy strategy n) = G.success strategy ^ n := by
unfold success
change ((G.questions.iid n).transport (tupleQuestionEquiv n)).probability _ = _
rw [FiniteDistribution.probability_transport]
exact G.questions.probability_iid_all (G.wins strategy) n
@[simp] theorem repetition_question_weight (G : Game Q₁ Q₂ A₁ A₂) (n : Nat)
(questions : (Fin n → Q₁) × (Fin n → Q₂)) :
(G.repetition n).questions.weight questions =
∏ i, G.questions.weight (questions.1 i, questions.2 i) := rfl
@[simp] theorem repetition_accepts_iff (G : Game Q₁ Q₂ A₁ A₂) (n : Nat)
(x : Fin n → Q₁) (y : Fin n → Q₂) (a : Fin n → A₁) (b : Fin n → A₂) :
(G.repetition n).accepts x y a b = true ↔
∀ i, G.accepts (x i) (y i) (a i) (b i) = true := by
classical
simp [repetition]
def coordinateWin (G : Game Q₁ Q₂ A₁ A₂) {n : Nat}
(strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂))
(coordinate : Fin n) (questions : (Fin n → Q₁) × (Fin n → Q₂)) : Bool :=
G.accepts (questions.1 coordinate) (questions.2 coordinate)
(strategy.1 questions.1 coordinate) (strategy.2 questions.2 coordinate)
def selectedWins (G : Game Q₁ Q₂ A₁ A₂) {n : Nat}
(strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂))
(selected : Finset (Fin n)) (questions : (Fin n → Q₁) × (Fin n → Q₂)) : Bool := by
classical
exact decide (∀ i ∈ selected, G.coordinateWin strategy i questions = true)
theorem selectedWins_mono (G : Game Q₁ Q₂ A₁ A₂) {n : Nat}
(strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂))
{selected selected' : Finset (Fin n)} (h : selected ⊆ selected') :
(G.repetition n).questions.probability (G.selectedWins strategy selected') ≤
(G.repetition n).questions.probability (G.selectedWins strategy selected) := by
apply FiniteDistribution.probability_mono
intro questions hwin
simp only [selectedWins, decide_eq_true_eq] at hwin ⊢
intro i hi
exact hwin i (h hi)
@[simp] theorem selectedWins_empty (G : Game Q₁ Q₂ A₁ A₂) {n : Nat}
(strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂))
(questions : (Fin n → Q₁) × (Fin n → Q₂)) :
G.selectedWins strategy ∅ questions = true := by
simp [selectedWins]
theorem selectedWins_univ (G : Game Q₁ Q₂ A₁ A₂) {n : Nat}
(strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂)) :
G.selectedWins strategy Finset.univ = (G.repetition n).wins strategy := by
classical
funext questions
simp [selectedWins, coordinateWin, repetition, wins]
variable {Q₁ Q₂ A₁ A₂ : Type*}
[Fintype Q₁] [Fintype Q₂] [Fintype A₁] [Fintype A₂]
[Nonempty A₁] [Nonempty A₂]
def value (G : Game Q₁ Q₂ A₁ A₂) : ℝ := by
classical
exact Finset.univ.sup' Finset.univ_nonempty G.success
theorem success_le_value (G : Game Q₁ Q₂ A₁ A₂)
(strategy : Strategy Q₁ Q₂ A₁ A₂) : G.success strategy ≤ G.value := by
classical
exact Finset.le_sup' G.success (Finset.mem_univ strategy)
theorem value_le_iff (G : Game Q₁ Q₂ A₁ A₂) (bound : ℝ) :
G.value ≤ bound ↔ ∀ strategy : Strategy Q₁ Q₂ A₁ A₂, G.success strategy ≤ bound := by
classical
simp [value, Finset.sup'_le_iff]
theorem exists_optimal_strategy (G : Game Q₁ Q₂ A₁ A₂) :
∃ strategy : Strategy Q₁ Q₂ A₁ A₂, G.success strategy = G.value := by
classical
obtain ⟨strategy, _, h⟩ := Finset.exists_mem_eq_sup'
(s := (Finset.univ : Finset (Strategy Q₁ Q₂ A₁ A₂))) Finset.univ_nonempty G.success
exact ⟨strategy, h.symm⟩
theorem value_nonnegative (G : Game Q₁ Q₂ A₁ A₂) : 0 ≤ G.value := by
obtain ⟨strategy, h⟩ := G.exists_optimal_strategy
rw [← h]
exact G.success_nonnegative strategy
theorem value_le_one (G : Game Q₁ Q₂ A₁ A₂) : G.value ≤ 1 :=
(G.value_le_iff 1).2 G.success_le_one
theorem randomized_success_le_value (G : Game Q₁ Q₂ A₁ A₂)
{Seed : Type*} [Fintype Seed] (seedLaw : FiniteDistribution Seed)
(strategies : Seed → Strategy Q₁ Q₂ A₁ A₂) :
seedLaw.expectation (fun seed => G.success (strategies seed)) ≤ G.value := by
unfold FiniteDistribution.expectation
calc
_ ≤ ∑ seed, seedLaw.weight seed * G.value := by
apply Finset.sum_le_sum
intro seed _
exact mul_le_mul_of_nonneg_left (G.success_le_value _) (seedLaw.nonnegative seed)
_ = G.value := by rw [← Finset.sum_mul, seedLaw.normalized, one_mul]
omit [Nonempty A₁] [Nonempty A₂] in
theorem success_repetition_zero (G : Game Q₁ Q₂ A₁ A₂)
(strategy : Strategy (Fin 0 → Q₁) (Fin 0 → Q₂) (Fin 0 → A₁) (Fin 0 → A₂)) :
(G.repetition 0).success strategy = 1 := by
have h : (G.repetition 0).wins strategy = fun _ => true := by
funext questions
simp [wins, repetition]
unfold success
rw [h, FiniteDistribution.probability_true]
@[simp] theorem value_repetition_zero (G : Game Q₁ Q₂ A₁ A₂) :
(G.repetition 0).value = 1 := by
obtain ⟨strategy, h⟩ := (G.repetition 0).exists_optimal_strategy
rw [← h]
exact G.success_repetition_zero strategy
theorem pow_value_le_repetition_value (G : Game Q₁ Q₂ A₁ A₂) (n : Nat) :
G.value ^ n ≤ (G.repetition n).value := by
obtain ⟨strategy, h⟩ := G.exists_optimal_strategy
rw [← h, ← G.success_repeatStrategy strategy n]
exact (G.repetition n).success_le_value (repeatStrategy strategy n)
theorem value_le_of_localSimulation {R₁ R₂ B₁ B₂ : Type*}
[Fintype R₁] [Fintype R₂] [Fintype B₁] [Fintype B₂]
[Nonempty B₁] [Nonempty B₂]
(G : Game Q₁ Q₂ A₁ A₂) (H : Game R₁ R₂ B₁ B₂)
(questionMap₁ : Q₁ → R₁) (questionMap₂ : Q₂ → R₂)
(answerMap₁ : Q₁ → B₁ → A₁) (answerMap₂ : Q₂ → B₂ → A₂)
(questionLaw : H.questions =
G.questions.pushforward (fun q => (questionMap₁ q.1, questionMap₂ q.2)))
(acceptance : ∀ x y a b,
H.accepts (questionMap₁ x) (questionMap₂ y) a b = true →
G.accepts x y (answerMap₁ x a) (answerMap₂ y b) = true) :
H.value ≤ G.value := by
apply (H.value_le_iff _).2
intro strategy
exact (G.success_le_of_localSimulation H questionMap₁ questionMap₂
answerMap₁ answerMap₂ questionLaw acceptance strategy).trans (G.success_le_value _)
end Game
namespace FiniteDistribution
variable {Ω Γ Q A : Type*} [Fintype Ω] [Fintype Γ] [Fintype Q] [Fintype A]
theorem eq_of_weight_eq {μ ν : FiniteDistribution Ω}
(h : ∀ x, μ.weight x = ν.weight x) : μ = ν := by
cases μ with
| mk w hw hs =>
cases ν with
| mk w' hw' hs' =>
have he : w = w' := funext h
cases he
rfl
def table [DecidableEq Q] (responses : Q → FiniteDistribution A) :
FiniteDistribution (Q → A) := by
classical
exact
{ weight := fun answers => ∏ q, (responses q).weight (answers q)
nonnegative := fun answers => Finset.prod_nonneg fun q _ =>
(responses q).nonnegative (answers q)
normalized := by
rw [← Fintype.prod_sum]
simp only [FiniteDistribution.normalized, Finset.prod_const_one] }
theorem expectation_table_eval [DecidableEq Q] (responses : Q → FiniteDistribution A)
(q₀ : Q) (h : A → ℝ) :
(table responses).expectation (fun answers => h (answers q₀)) =
(responses q₀).expectation h := by
classical
change (∑ answers : Q → A,
(∏ q, (responses q).weight (answers q)) * h (answers q₀)) =
∑ a, (responses q₀).weight a * h a
calc
_ = ∑ answers : Q → A,
∏ q, (responses q).weight (answers q) *
(if q = q₀ then h (answers q) else 1) := by
apply Finset.sum_congr rfl
intro answers _
rw [Finset.prod_mul_distrib]
simp
_ = ∏ q, ∑ a, (responses q).weight a * (if q = q₀ then h a else 1) :=
(Fintype.prod_sum (fun q a =>
(responses q).weight a * (if q = q₀ then h a else 1))).symm
_ = ∏ q : Q, if q = q₀ then (∑ a, (responses q₀).weight a * h a) else 1 := by
apply Finset.prod_congr rfl
intro q _
by_cases hq : q = q₀
· subst q
simp
· simp [hq, (responses q).normalized]
_ = _ := by simp
theorem table_eval_pushforward [DecidableEq Q]
(responses : Q → FiniteDistribution A) (q₀ : Q) :
(table responses).pushforward (fun answers => answers q₀) = responses q₀ := by
classical
apply eq_of_weight_eq
intro a
calc
_ = (table responses).expectation
(fun answers => if answers q₀ = a then 1 else 0) := by
simp [pushforward, expectation, mul_ite]
_ = (responses q₀).expectation (fun b => if b = a then 1 else 0) :=
expectation_table_eval responses q₀ (fun b => if b = a then (1 : ℝ) else 0)
_ = _ := by simp [expectation, mul_ite]
def product (μ : FiniteDistribution Ω) (ν : FiniteDistribution Γ) :
FiniteDistribution (Ω × Γ) where
weight x := μ.weight x.1 * ν.weight x.2
nonnegative x := mul_nonneg (μ.nonnegative _) (ν.nonnegative _)
normalized := by
rw [Fintype.sum_prod_type]
simp_rw [← Finset.mul_sum, ν.normalized, mul_one]
exact μ.normalized
theorem expectation_product (μ : FiniteDistribution Ω) (ν : FiniteDistribution Γ)
(f : Ω × Γ → ℝ) :
(μ.product ν).expectation f =
μ.expectation (fun x => ν.expectation (fun y => f (x,y))) := by
simp only [expectation, product, Fintype.sum_prod_type, Finset.mul_sum, mul_assoc]
theorem expectation_comm (μ : FiniteDistribution Ω) (ν : FiniteDistribution Γ)
(f : Ω → Γ → ℝ) :
μ.expectation (fun x => ν.expectation (f x)) =
ν.expectation (fun y => μ.expectation (fun x => f x y)) := by
unfold expectation
simp_rw [Finset.mul_sum]
rw [Finset.sum_comm]
apply Finset.sum_congr rfl
intro y _
apply Finset.sum_congr rfl
intro x _
exact mul_left_comm _ _ _
theorem expectation_congr (μ : FiniteDistribution Ω) {f g : Ω → ℝ}
(h : ∀ x, f x = g x) : μ.expectation f = μ.expectation g := by
unfold expectation
apply Finset.sum_congr rfl
intro x _
rw [h x]
end FiniteDistribution
namespace Game
variable {Q₁ Q₂ A₁ A₂ : Type*}
[Fintype Q₁] [Fintype Q₂] [Fintype A₁] [Fintype A₂]
[DecidableEq Q₁] [DecidableEq Q₂]
def responseTableLaw (responses₁ : Q₁ → FiniteDistribution A₁)
(responses₂ : Q₂ → FiniteDistribution A₂) :
FiniteDistribution (Strategy Q₁ Q₂ A₁ A₂) := by
classical
exact (FiniteDistribution.table responses₁).product (FiniteDistribution.table responses₂)
def stochasticSuccess (G : Game Q₁ Q₂ A₁ A₂)
(responses₁ : Q₁ → FiniteDistribution A₁)
(responses₂ : Q₂ → FiniteDistribution A₂) : ℝ :=
G.questions.expectation (fun q =>
(responses₁ q.1).expectation (fun a =>
(responses₂ q.2).expectation (fun b =>
if G.accepts q.1 q.2 a b then 1 else 0)))
omit [DecidableEq Q₁] [DecidableEq Q₂] in
theorem success_eq_question_expectation (G : Game Q₁ Q₂ A₁ A₂)
(strategy : Strategy Q₁ Q₂ A₁ A₂) :
G.success strategy = G.questions.expectation
(fun q => if G.wins strategy q then 1 else 0) := by
simp [success, FiniteDistribution.probability,
FiniteDistribution.expectation, mul_ite]
theorem table_success_eq_stochastic (G : Game Q₁ Q₂ A₁ A₂)
(responses₁ : Q₁ → FiniteDistribution A₁)
(responses₂ : Q₂ → FiniteDistribution A₂) :
(responseTableLaw responses₁ responses₂).expectation G.success =
G.stochasticSuccess responses₁ responses₂ := by
classical
unfold stochasticSuccess
calc
_ = (responseTableLaw responses₁ responses₂).expectation
(fun strategy => G.questions.expectation
(fun q => if G.wins strategy q then 1 else 0)) :=
FiniteDistribution.expectation_congr _ (G.success_eq_question_expectation)
_ = G.questions.expectation (fun q =>
(responseTableLaw responses₁ responses₂).expectation
(fun strategy => if G.wins strategy q then 1 else 0)) :=
FiniteDistribution.expectation_comm _ _ _
_ = _ := by
apply FiniteDistribution.expectation_congr
intro q
rw [responseTableLaw, FiniteDistribution.expectation_product]
change (FiniteDistribution.table responses₁).expectation
(fun answers₁ => (FiniteDistribution.table responses₂).expectation
(fun answers₂ =>
if G.accepts q.1 q.2 (answers₁ q.1) (answers₂ q.2) then 1 else 0)) = _
calc
_ = (FiniteDistribution.table responses₁).expectation
(fun answers₁ => (responses₂ q.2).expectation
(fun b => if G.accepts q.1 q.2 (answers₁ q.1) b then 1 else 0)) := by
apply FiniteDistribution.expectation_congr
intro answers₁
exact FiniteDistribution.expectation_table_eval responses₂ q.2
(fun b => if G.accepts q.1 q.2 (answers₁ q.1) b then (1 : ℝ) else 0)
_ = _ := FiniteDistribution.expectation_table_eval responses₁ q.1
(fun a => (responses₂ q.2).expectation
(fun b => if G.accepts q.1 q.2 a b then (1 : ℝ) else 0))
variable [Nonempty A₁] [Nonempty A₂]
theorem stochasticSuccess_le_value (G : Game Q₁ Q₂ A₁ A₂)
(responses₁ : Q₁ → FiniteDistribution A₁)
(responses₂ : Q₂ → FiniteDistribution A₂) :
G.stochasticSuccess responses₁ responses₂ ≤ G.value := by
classical
rw [← G.table_success_eq_stochastic]
exact G.randomized_success_le_value (responseTableLaw responses₁ responses₂) id
theorem exists_deterministic_ge_stochastic (G : Game Q₁ Q₂ A₁ A₂)
(responses₁ : Q₁ → FiniteDistribution A₁)
(responses₂ : Q₂ → FiniteDistribution A₂) :
∃ strategy : Strategy Q₁ Q₂ A₁ A₂,
G.stochasticSuccess responses₁ responses₂ ≤ G.success strategy := by
obtain ⟨strategy, h⟩ := G.exists_optimal_strategy
refine ⟨strategy, ?_⟩
rw [h]
exact G.stochasticSuccess_le_value responses₁ responses₂
end Game
end
end MinUncutGames.Foundations.Games
end OAI