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Add lean source and binary files (part 64)
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import Mathlib
import OAI.Computability.VertexCover.Games.Value
import OAI.Computability.VertexCover.Games.TotalVariation
import OAI.Computability.VertexCover.Games.Mixture
namespace OAI
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namespace UniqueGames.Foundations.Games.Game
noncomputable section
variable {Q₁ Q₂ A₁ A₂ R₁ R₂ B₁ B₂ Seed : Type*}
[Fintype Q₁] [Fintype Q₂] [Fintype A₁] [Fintype A₂]
[Fintype R₁] [Fintype R₂] [Fintype B₁] [Fintype B₂] [Fintype Seed]
[Nonempty A₁] [Nonempty A₂]
def localEmbeddingLaw (G : Game Q₁ Q₂ A₁ A₂)
(seedLaw : FiniteDistribution Seed)
(left : Seed → Q₁ → R₁) (right : Seed → Q₂ → R₂) :
FiniteDistribution (R₁ × R₂) :=
seedLaw.mixture fun seed =>
G.questions.pushforward fun q => (left seed q.1, right seed q.2)
theorem success_le_value_add_embedding_distance
(G : Game Q₁ Q₂ A₁ A₂) (H : Game R₁ R₂ B₁ B₂)
(seedLaw : FiniteDistribution Seed)
(left : Seed → Q₁ → R₁) (right : Seed → Q₂ → R₂)
(answerLeft : Seed → Q₁ → B₁ → A₁)
(answerRight : Seed → Q₂ → B₂ → A₂)
(acceptance : ∀ seed x y a b,
H.accepts (left seed x) (right seed y) a b = true →
G.accepts x y (answerLeft seed x a) (answerRight seed y b) = true)
(strategy : Strategy R₁ R₂ B₁ B₂) :
H.success strategy ≤ G.value +
H.questions.totalVariation (G.localEmbeddingLaw seedLaw left right) := by
have localBound (seed : Seed) :
(G.questions.pushforward (fun q => (left seed q.1, right seed q.2))).probability
(H.wins strategy) ≤ G.value := by
let embedded : Game R₁ R₂ B₁ B₂ :=
{ questions := G.questions.pushforward fun q => (left seed q.1, right seed q.2)
accepts := H.accepts }
change embedded.success strategy ≤ G.value
exact (G.success_le_of_localSimulation embedded (left seed) (right seed)
(answerLeft seed) (answerRight seed) rfl (acceptance seed) strategy).trans
(G.success_le_value _)
have mixtureBound :
(G.localEmbeddingLaw seedLaw left right).probability (H.wins strategy) ≤ G.value :=
seedLaw.probability_mixture_le _ _ _ localBound
exact (H.questions.probability_le_add_totalVariation
(G.localEmbeddingLaw seedLaw left right) (H.wins strategy)).trans
(add_le_add mixtureBound (le_refl _))
def coordinateGame (G : Game Q₁ Q₂ A₁ A₂) {n : Nat} (coordinate : Fin n)
(law : FiniteDistribution ((Fin n → Q₁) × (Fin n → Q₂))) :
Game (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂) where
questions := law
accepts x y a b := G.accepts (x coordinate) (y coordinate) (a coordinate) (b coordinate)
theorem coordinate_probability_le_value_add_embedding_distance
(G : Game Q₁ Q₂ A₁ A₂) {n : Nat} (coordinate : Fin n)
(law : FiniteDistribution ((Fin n → Q₁) × (Fin n → Q₂)))
(seedLaw : FiniteDistribution Seed)
(left : Seed → Q₁ → Fin n → Q₁) (right : Seed → Q₂ → Fin n → Q₂)
(left_preserves : ∀ seed x, left seed x coordinate = x)
(right_preserves : ∀ seed y, right seed y coordinate = y)
(strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂)) :
law.probability (G.coordinateWin strategy coordinate) ≤ G.value +
law.totalVariation (G.localEmbeddingLaw seedLaw left right) := by
apply G.success_le_value_add_embedding_distance (G.coordinateGame coordinate law)
seedLaw left right (fun _ _ a => a coordinate) (fun _ _ b => b coordinate)
intro seed x y a b h
simpa only [coordinateGame, left_preserves, right_preserves] using h
theorem coordinate_probability_le_value_of_approximate_embeddings
{SeedFamily : Nat → Type*} [∀ t, Fintype (SeedFamily t)]
(G : Game Q₁ Q₂ A₁ A₂) {n : Nat} (coordinate : Fin n)
(law : FiniteDistribution ((Fin n → Q₁) × (Fin n → Q₂)))
(seedLaw : (t : Nat) → FiniteDistribution (SeedFamily t))
(left : (t : Nat) → SeedFamily t → Q₁ → Fin n → Q₁)
(right : (t : Nat) → SeedFamily t → Q₂ → Fin n → Q₂)
(left_preserves : ∀ t seed x, left t seed x coordinate = x)
(right_preserves : ∀ t seed y, right t seed y coordinate = y)
(strategy : Strategy (Fin n → Q₁) (Fin n → Q₂) (Fin n → A₁) (Fin n → A₂))
(distance : ℝ)
(close : ∀ η : ℝ, 0 < η → ∃ t,
law.totalVariation (G.localEmbeddingLaw (seedLaw t) (left t) (right t)) ≤
distance + η) :
law.probability (G.coordinateWin strategy coordinate) ≤ G.value + distance := by
by_contra h
have gap : 0 < law.probability (G.coordinateWin strategy coordinate) -
(G.value + distance) := sub_pos.mpr (lt_of_not_ge h)
obtain ⟨t, ht⟩ := close
((law.probability (G.coordinateWin strategy coordinate) - (G.value + distance)) / 2)
(by linarith)
have bound := G.coordinate_probability_le_value_add_embedding_distance coordinate law
(seedLaw t) (left t) (right t) (left_preserves t) (right_preserves t) strategy
linarith
end
end UniqueGames.Foundations.Games.Game
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end
end OAI