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import OAI.Computability.MeanPayoff.Traversal
namespace OAI
section
namespace MeanPayoff
namespace RandomTree
theorem map_bind {α β γ : Type} (t : RandomTree α) (f : α → RandomTree β) (g : β → γ) :
(t.bind f).map g = t.bind (fun a => (f a).map g) := by
induction t with
| leaf a => rfl
| coin l r il ir => simpa only [map, bind] using congrArg₂ coin il ir
theorem failure_and_metadata {α : Type} (t : RandomTree α) (A B : α → Prop) (h : t.All A) :
t.probability (fun a => ¬(A a ∧ B a)) ≤ t.probability (fun a => ¬B a) := by
apply probability_mono_all
exact all_mono t h (fun a ha hf hb => hf ⟨ha, hb⟩)
end RandomTree
def nodeError (n Bmax : ℕ) : ℚ :=
(2 * (n : ℚ) * Bmax + globalListBound n Bmax + 3) * epsilon n Bmax
theorem nodeError_nonneg (n Bmax : ℕ) : 0 ≤ nodeError n Bmax := by
unfold nodeError
exact mul_nonneg (by positivity) (epsilon_nonneg _ _)
theorem orientStage_high (G : Game) {Bmax : ℕ} (P : Budgets G.n) (hR : 1 ≤ P.parameter)
(lower : LowerSolver (Bmax := Bmax) P) (hl : LowerComparisons G P lower)
(I : SolveBox G.n Bmax) (hB : 128 * globalS Bmax < I.width)
(up : RandomTree (BoxVector (I.capHigh I.C I.C_positive (I.C_smaller hB).le)))
(lo : RandomTree (BoxVector (I.capLow I.C I.C_positive (I.C_smaller hB).le)))
{δ : ℚ} (hδ : 0 ≤ δ)
(hup : HighAccuracy G P _ up δ) (hlo : HighAccuracy G P _ lo δ)
(y : Vec (Fin G.n)) (hy : AdmissibleSub (operator G) I.a I.b y P)
(hc : (I.C : ℤ) < deviation G y I.a → (4 / 5) * P.k < mass P.alpha (highCore I y)) :
((orientPlus (orient G P hR lower I) (globalJ G.n Bmax)).bind
(fun O => finishChoice G P hR lower I hB O up lo)).probability (fun p => ¬y ≤ p.val) ≤
((globalListBound G.n Bmax : ℚ) + 1) * epsilon G.n Bmax + δ := by
let t := orientPlus (orient G P hR lower I) (globalJ G.n Bmax)
let A := fun O : Orientation P => O.exceptions.length ≤ globalListBound G.n Bmax
let B := fun O : Orientation P => (I.C : ℤ) < deviation G y I.a → HighAlternative I P y O
have he := epsilon_nonneg G.n Bmax
have ht : t.probability (fun O => ¬(A O ∧ B O)) ≤ epsilon G.n Bmax := by
apply (RandomTree.failure_and_metadata t A B (orientPlus_length G P hR lower I)).trans
apply RandomTree.imp_error t _ _ he
intro hd
exact orientPlus_high G P hR lower hl I y hy (hc hd)
apply le_trans (RandomTree.bind_error t (fun O => finishChoice G P hR lower I hB O up lo)
(fun O => A O ∧ B O) (fun p : BoxVector I => ¬y ≤ p.val)
(ε := (globalListBound G.n Bmax : ℚ) * epsilon G.n Bmax + δ)
(add_nonneg (mul_nonneg (Nat.cast_nonneg _) he) hδ) ht ?_) (by ring_nf; rfl)
intro O hO
apply (finishChoice_high G P hR lower hl I hB O up lo hδ hup hlo y hy hO.2).trans
exact add_le_add (mul_le_mul_of_nonneg_right (Nat.cast_le.mpr hO.1) he) le_rfl
theorem orientStage_low (G : Game) {Bmax : ℕ} (P : Budgets G.n) (hR : 1 ≤ P.parameter)
(lower : LowerSolver (Bmax := Bmax) P) (hl : LowerComparisons G P lower)
(I : SolveBox G.n Bmax) (hB : 128 * globalS Bmax < I.width)
(up : RandomTree (BoxVector (I.capHigh I.C I.C_positive (I.C_smaller hB).le)))
(lo : RandomTree (BoxVector (I.capLow I.C I.C_positive (I.C_smaller hB).le)))
{δ : ℚ} (hδ : 0 ≤ δ)
(hup : LowAccuracy G P _ up δ) (hlo : LowAccuracy G P _ lo δ)
(z : Vec (Fin G.n)) (hz : AdmissibleSuper (operator G) I.a I.b z P)
(hc : (I.C : ℤ) < deviation G I.b z → (4 / 5) * P.m < mass P.beta (lowCore I z)) :
((orientPlus (orient G P hR lower I) (globalJ G.n Bmax)).bind
(fun O => finishChoice G P hR lower I hB O up lo)).probability (fun p => ¬p.val ≤ z) ≤
((globalListBound G.n Bmax : ℚ) + 1) * epsilon G.n Bmax + δ := by
let t := orientPlus (orient G P hR lower I) (globalJ G.n Bmax)
let A := fun O : Orientation P => O.exceptions.length ≤ globalListBound G.n Bmax
let B := fun O : Orientation P => (I.C : ℤ) < deviation G I.b z → LowAlternative I P z O
have he := epsilon_nonneg G.n Bmax
have ht : t.probability (fun O => ¬(A O ∧ B O)) ≤ epsilon G.n Bmax := by
apply (RandomTree.failure_and_metadata t A B (orientPlus_length G P hR lower I)).trans
apply RandomTree.imp_error t _ _ he
intro hd
exact orientPlus_low G P hR lower hl I z hz (hc hd)
apply le_trans (RandomTree.bind_error t (fun O => finishChoice G P hR lower I hB O up lo)
(fun O => A O ∧ B O) (fun p : BoxVector I => ¬p.val ≤ z)
(ε := (globalListBound G.n Bmax : ℚ) * epsilon G.n Bmax + δ)
(add_nonneg (mul_nonneg (Nat.cast_nonneg _) he) hδ) ht ?_) (by ring_nf; rfl)
intro O hO
apply (finishChoice_low G P hR lower hl I hB O up lo hδ hup hlo z hz hO.2).trans
exact add_le_add (mul_le_mul_of_nonneg_right (Nat.cast_le.mpr hO.1) he) le_rfl
theorem node_error_step {n Bmax : ℕ} (I : SolveBox n Bmax) :
(2 * (volume I.b I.a : ℚ) + 2) * epsilon n Bmax +
(((globalListBound n Bmax : ℚ) + 1) * epsilon n Bmax +
((I.width - 1 : ℕ) : ℚ) * nodeError n Bmax) ≤ (I.width : ℚ) * nodeError n Bmax := by
have he := epsilon_nonneg n Bmax
have hv : (volume I.b I.a : ℚ) ≤ (n : ℚ) * Bmax := by exact_mod_cast I.volume_le
have hp : ((I.width - 1 : ℕ) : ℚ) + 1 = I.width := by
exact_mod_cast Nat.sub_add_cancel I.positive
calc
_ = (2 * (volume I.b I.a : ℚ) + globalListBound n Bmax + 3) * epsilon n Bmax +
((I.width - 1 : ℕ) : ℚ) * nodeError n Bmax := by ring
_ ≤ nodeError n Bmax + ((I.width - 1 : ℕ) : ℚ) * nodeError n Bmax := by
apply add_le_add _ le_rfl
exact mul_le_mul_of_nonneg_right (by linarith only [hv]) he
_ = _ := by rw [← hp]; ring
theorem solveWidth_high (G : Game) {Bmax : ℕ} (P : Budgets G.n) (hR : 1 ≤ P.parameter)
(lower : LowerSolver (Bmax := Bmax) P) (hl : LowerComparisons G P lower)
(I : SolveBox G.n Bmax) (y : Vec (Fin G.n))
(hy : AdmissibleSub (operator G) I.a I.b y P) :
(solveWidth G P hR lower I).probability (fun p => ¬y ≤ p.val) ≤
(I.width : ℚ) * nodeError G.n Bmax := by
by_cases hsmall : I.width ≤ 128 * globalS Bmax
· have hc : y ≤ (I.exactVector G).val := box_comparison G hy.1 (basic_spec G I.a I.b I.ordered).2.1
rw [solveWidth, dite_eq_left hsmall, RandomTree.probability_leaf, ite_eq_right (not_not_intro hc)]
exact mul_nonneg (Nat.cast_nonneg _) (nodeError_nonneg _ _)
· have hB : 128 * globalS Bmax < I.width := lt_of_not_ge hsmall
rw [solveWidth, dite_eq_right hsmall]
dsimp only
let δ : ℚ := ((I.width - 1 : ℕ) : ℚ) * nodeError G.n Bmax
have hδ : 0 ≤ δ := mul_nonneg (Nat.cast_nonneg _) (nodeError_nonneg _ _)
have he := epsilon_nonneg G.n Bmax
apply le_trans (RandomTree.bind_error (tighten P hR lower I hB) _
(TightHigh G P y) (fun p : BoxVector I => ¬y ≤ p.val)
(ε := ((globalListBound G.n Bmax : ℚ) + 1) * epsilon G.n Bmax + δ)
(add_nonneg (mul_nonneg (by positivity) he) hδ)
(tighten_high G P hR lower hl I hB y hy) ?_) (node_error_step I)
intro T hT
obtain ⟨u, hyu, hu, hcore⟩ := hT
let K := T.box
have hK : 128 * globalS Bmax < K.width := by change 128 * globalS Bmax < T.box.width; rw [T.width_eq]; exact hB
let up := solveWidth G P hR lower (K.capHigh K.C K.C_positive (K.C_smaller hK).le)
let lo := solveWidth G P hR lower (K.capLow K.C K.C_positive (K.C_smaller hK).le)
have hc : K.C ≤ I.width - 1 := by have hh := K.C_smaller hK; have hw := T.width_eq; dsimp [K] at hh ⊢; omega
have hup : HighAccuracy G P _ up δ := by
intro v hv
apply (solveWidth_high G P hR lower hl (K.capHigh K.C K.C_positive (K.C_smaller hK).le) v hv).trans
exact mul_le_mul_of_nonneg_right (Nat.cast_le.mpr hc) (nodeError_nonneg _ _)
have hlo : HighAccuracy G P _ lo δ := by
intro v hv
apply (solveWidth_high G P hR lower hl (K.capLow K.C K.C_positive (K.C_smaller hK).le) v hv).trans
exact mul_le_mul_of_nonneg_right (Nat.cast_le.mpr hc) (nodeError_nonneg _ _)
change ((orientPlus (orient G P hR lower K) (globalJ G.n Bmax)).bind
(fun O => (finishChoice G P hR lower K hK O up lo).map T.include)).probability
(fun p => ¬y ≤ p.val) ≤ _
rw [← RandomTree.map_bind]
apply RandomTree.map_error _ T.include (fun p : BoxVector K => u ≤ p.val) _
(orientStage_high G P hR lower hl K hK up lo hδ hup hlo u hu hcore)
intro p hp hf
exact hf (hyu.trans hp)
termination_by I.width
decreasing_by
all_goals
change K.C < I.width
rw [← T.width_eq]
exact K.C_smaller hK
theorem solveWidth_low (G : Game) {Bmax : ℕ} (P : Budgets G.n) (hR : 1 ≤ P.parameter)
(lower : LowerSolver (Bmax := Bmax) P) (hl : LowerComparisons G P lower)
(I : SolveBox G.n Bmax) (z : Vec (Fin G.n))
(hz : AdmissibleSuper (operator G) I.a I.b z P) :
(solveWidth G P hR lower I).probability (fun p => ¬p.val ≤ z) ≤
(I.width : ℚ) * nodeError G.n Bmax := by
by_cases hsmall : I.width ≤ 128 * globalS Bmax
· have hc : (I.exactVector G).val ≤ z := box_comparison G (basic_spec G I.a I.b I.ordered).1 hz.1
rw [solveWidth, dite_eq_left hsmall, RandomTree.probability_leaf, ite_eq_right (not_not_intro hc)]
exact mul_nonneg (Nat.cast_nonneg _) (nodeError_nonneg _ _)
· have hB : 128 * globalS Bmax < I.width := lt_of_not_ge hsmall
rw [solveWidth, dite_eq_right hsmall]
dsimp only
let δ : ℚ := ((I.width - 1 : ℕ) : ℚ) * nodeError G.n Bmax
have hδ : 0 ≤ δ := mul_nonneg (Nat.cast_nonneg _) (nodeError_nonneg _ _)
have he := epsilon_nonneg G.n Bmax
apply le_trans (RandomTree.bind_error (tighten P hR lower I hB) _
(TightLow G P z) (fun p : BoxVector I => ¬p.val ≤ z)
(ε := ((globalListBound G.n Bmax : ℚ) + 1) * epsilon G.n Bmax + δ)
(add_nonneg (mul_nonneg (by positivity) he) hδ)
(tighten_low G P hR lower hl I hB z hz) ?_) (node_error_step I)
intro T hT
obtain ⟨u, huz, hu, hcore⟩ := hT
let K := T.box
have hK : 128 * globalS Bmax < K.width := by change 128 * globalS Bmax < T.box.width; rw [T.width_eq]; exact hB
let up := solveWidth G P hR lower (K.capHigh K.C K.C_positive (K.C_smaller hK).le)
let lo := solveWidth G P hR lower (K.capLow K.C K.C_positive (K.C_smaller hK).le)
have hc : K.C ≤ I.width - 1 := by have hh := K.C_smaller hK; have hw := T.width_eq; dsimp [K] at hh ⊢; omega
have hup : LowAccuracy G P _ up δ := by
intro v hv
apply (solveWidth_low G P hR lower hl (K.capHigh K.C K.C_positive (K.C_smaller hK).le) v hv).trans
exact mul_le_mul_of_nonneg_right (Nat.cast_le.mpr hc) (nodeError_nonneg _ _)
have hlo : LowAccuracy G P _ lo δ := by
intro v hv
apply (solveWidth_low G P hR lower hl (K.capLow K.C K.C_positive (K.C_smaller hK).le) v hv).trans
exact mul_le_mul_of_nonneg_right (Nat.cast_le.mpr hc) (nodeError_nonneg _ _)
change ((orientPlus (orient G P hR lower K) (globalJ G.n Bmax)).bind
(fun O => (finishChoice G P hR lower K hK O up lo).map T.include)).probability
(fun p => ¬p.val ≤ z) ≤ _
rw [← RandomTree.map_bind]
apply RandomTree.map_error _ T.include (fun p : BoxVector K => p.val ≤ u) _
(orientStage_low G P hR lower hl K hK up lo hδ hup hlo u hu hcore)
intro p hp hf
exact hf (hp.trans huz)
termination_by I.width
decreasing_by
all_goals
change K.C < I.width
rw [← T.width_eq]
exact K.C_smaller hK
theorem root_error_coefficient (n Bmax : ℕ) :
Bmax * (2 * n * Bmax + globalListBound n Bmax + 3) * 16 ≤ 2 ^ globalJ n Bmax := by
by_cases hB : Bmax = 0
· simp [hB]
have hb : 1 ≤ Bmax := by omega
let s := globalS Bmax
let k := s * (n + 1)
have hs : 16 ≤ s := globalS_large Bmax
have hsk : s ≤ k := by dsimp [k]; nlinarith
have hk : 16 ≤ k := hs.trans hsk
have hn : n ≤ k := by dsimp [k]; nlinarith
have hg : globalG Bmax ≤ s := by
have h := globalS_lower Bmax
change 131072 * (globalG Bmax + 1) ≤ s at h
omega
have hclog : Nat.clog 2 (Bmax + 1) ≤ s := by unfold globalG at hg; omega
have hBs : Bmax ≤ 2 ^ s :=
(Nat.le_succ Bmax).trans ((Nat.clog_le_iff_le_pow (by norm_num)).mp hclog)
have hk6 : k ^ 2 ≤ k ^ 6 := Nat.pow_le_pow_right (by omega) (by norm_num)
have hk7 : k ^ 2 ≤ k ^ 7 := Nat.pow_le_pow_right (by omega) (by norm_num)
have hJ : globalJ n Bmax ≤ 3 * k ^ 6 := by
have hpow : 1 ≤ k ^ 6 := Nat.one_le_pow _ _ (by omega)
change 2 * k ^ 6 + 1 ≤ 3 * k ^ 6
omega
have hM : globalListBound n Bmax ≤ 9 * k ^ 7 := by
have hfac : 2 * globalG Bmax + 3 ≤ 3 * k := by omega
calc
_ ≤ (3 * k ^ 6) * (3 * k) := Nat.mul_le_mul hJ hfac
_ = 9 * k ^ 7 := by ring
have hpoly : 2 * n + globalListBound n Bmax + 3 ≤ 10 * k ^ 7 := by
have hx : 2 * n + 3 ≤ k ^ 7 := by nlinarith
omega
have hpowK : k ≤ 2 ^ k := Nat.le_of_lt Nat.lt_two_pow_self
have hten : 10 ≤ 2 ^ (3 * k) := by
apply le_trans (show 10 ≤ 2 ^ 4 by norm_num)
exact Nat.pow_le_pow_right (by norm_num) (by omega)
have hpolyExp : 10 * k ^ 7 ≤ 2 ^ (10 * k) := by
calc
_ ≤ 2 ^ (3 * k) * (2 ^ k) ^ 7 := Nat.mul_le_mul hten (Nat.pow_le_pow_left hpowK 7)
_ = 2 ^ (10 * k) := by
rw [← pow_mul, ← pow_add, show 3 * k + k * 7 = 10 * k by omega]
have hN : Bmax * (2 * n * Bmax + globalListBound n Bmax + 3) ≤ 2 ^ (12 * k) := by
calc
_ ≤ Bmax ^ 2 * (2 * n + globalListBound n Bmax + 3) := by
have hscale : Bmax * (globalListBound n Bmax + 3) ≤
Bmax ^ 2 * (globalListBound n Bmax + 3) :=
Nat.mul_le_mul_right _ (by nlinarith : Bmax ≤ Bmax ^ 2)
nlinarith only [hscale]
_ ≤ (2 ^ s) ^ 2 * (10 * k ^ 7) := Nat.mul_le_mul (Nat.pow_le_pow_left hBs 2) hpoly
_ ≤ (2 ^ s) ^ 2 * 2 ^ (10 * k) := Nat.mul_le_mul_left _ hpolyExp
_ = 2 ^ (s * 2 + 10 * k) := by rw [← pow_mul, ← pow_add]
_ ≤ 2 ^ (12 * k) := Nat.pow_le_pow_right (by norm_num) (by omega)
have hAbsorb : 12 * k + 4 ≤ globalJ n Bmax := by
change 12 * k + 4 ≤ 2 * k ^ 6 + 1
nlinarith
calc
_ ≤ 2 ^ (12 * k) * 16 := Nat.mul_le_mul_right 16 hN
_ = 2 ^ (12 * k + 4) := by rw [pow_add]; rfl
_ ≤ 2 ^ globalJ n Bmax := Nat.pow_le_pow_right (by norm_num) hAbsorb
theorem root_error_small (n Bmax : ℕ) : (Bmax : ℚ) * nodeError n Bmax ≤ 1 / 16 := by
have h := root_error_coefficient n Bmax
have hq : ((Bmax : ℚ) * (2 * n * Bmax + globalListBound n Bmax + 3)) * 16 ≤
(2 : ℚ) ^ globalJ n Bmax := by exact_mod_cast h
have hp : 0 < (2 : ℚ) ^ globalJ n Bmax := pow_pos (by norm_num) _
dsimp [nodeError, epsilon]
rw [div_pow, one_pow, ← mul_assoc, mul_one_div, div_le_iff₀ hp]
linarith only [hq]
theorem width_error_small {n Bmax : ℕ} (I : SolveBox n Bmax) :
(I.width : ℚ) * nodeError n Bmax ≤ 1 / 16 := by
exact (mul_le_mul_of_nonneg_right (Nat.cast_le.mpr I.bounded)
(nodeError_nonneg _ _)).trans (root_error_small n Bmax)
end MeanPayoff
end
end OAI