LeanMachineLearning exposition

Learning.isStoppingTime_stepsUntil๐Ÿ”—

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Minimal Lean file

isStoppingTime_stepsUntil๐Ÿ”—

LemmaLearning.isStoppingTime_stepsUntil
Details

No docstring.

๐Ÿ”—theorem
Learning.isStoppingTime_stepsUntil.{u_1, u_2, u_3} {๐“ : Type u_1}
  {R : Type u_2} {ฮฉ : Type u_3} {m๐“ : MeasurableSpace ๐“}
  {mR : MeasurableSpace R} {mฮฉ : MeasurableSpace ฮฉ} [DecidableEq ๐“]
  {A : โ„• โ†’ ฮฉ โ†’ ๐“} {R' : โ„• โ†’ ฮฉ โ†’ R} {m : โ„•} [MeasurableSingletonClass ๐“]
  (hA : โˆ€ (n : โ„•), Measurable (A n))
  (hR' : โˆ€ (n : โ„•), Measurable (R' n)) (a : ๐“) (hm : m โ‰  0) :
  MeasureTheory.IsStoppingTime (IsAlgEnvSeq.filtration hA hR')
    (stepsUntil A a m)
Learning.isStoppingTime_stepsUntil.{u_1,
    u_2, u_3}
  {๐“ : Type u_1} {R : Type u_2}
  {ฮฉ : Type u_3} {m๐“ : MeasurableSpace ๐“}
  {mR : MeasurableSpace R}
  {mฮฉ : MeasurableSpace ฮฉ} [DecidableEq ๐“]
  {A : โ„• โ†’ ฮฉ โ†’ ๐“} {R' : โ„• โ†’ ฮฉ โ†’ R} {m : โ„•}
  [MeasurableSingletonClass ๐“]
  (hA : โˆ€ (n : โ„•), Measurable (A n))
  (hR' : โˆ€ (n : โ„•), Measurable (R' n))
  (a : ๐“) (hm : m โ‰  0) :
  MeasureTheory.IsStoppingTime
    (IsAlgEnvSeq.filtration hA hR')
    (stepsUntil A a m)

Code

lemma isStoppingTime_stepsUntil [MeasurableSingletonClass ๐“]
    (hA : โˆ€ n, Measurable (A n)) (hR' : โˆ€ n, Measurable (R' n)) (a : ๐“) (hm : m โ‰  0) :
    IsStoppingTime (IsAlgEnvSeq.filtration hA hR') (stepsUntil A a m)
Type uses (2)
Body uses (3)

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Proof
by
  rw [stepsUntil_eq_leastGE _ hm]
  refine StronglyAdapted.isStoppingTime_leastGE _ fun n โ†ฆ ?_
  suffices StronglyMeasurable[IsAlgEnvSeq.filtration hA hR' n] (pullCount A a (n + 1)) by
    fun_prop
  refine Measurable.stronglyMeasurable ?_
  exact adapted_pullCount_add_one hA hR' a n

Dependency graph

Type dependencies (2)

filtration๐Ÿ”—

DefinitionLearning.IsAlgEnvSeq.filtration
Details

Filtration generated by the history up to time n.

๐Ÿ”—def
Learning.IsAlgEnvSeq.filtration.{u_1, u_2, u_3} {๐“ : Type u_1}
  {๐“จ : Type u_2} {ฮฉ : Type u_3} {m๐“ : MeasurableSpace ๐“}
  {m๐“จ : MeasurableSpace ๐“จ} {mฮฉ : MeasurableSpace ฮฉ} {A : โ„• โ†’ ฮฉ โ†’ ๐“}
  {Y : โ„• โ†’ ฮฉ โ†’ ๐“จ} (hA : โˆ€ (n : โ„•), Measurable (A n))
  (hY : โˆ€ (n : โ„•), Measurable (Y n)) : MeasureTheory.Filtration โ„• mฮฉ
Learning.IsAlgEnvSeq.filtration.{u_1, u_2,
    u_3}
  {๐“ : Type u_1} {๐“จ : Type u_2}
  {ฮฉ : Type u_3} {m๐“ : MeasurableSpace ๐“}
  {m๐“จ : MeasurableSpace ๐“จ}
  {mฮฉ : MeasurableSpace ฮฉ} {A : โ„• โ†’ ฮฉ โ†’ ๐“}
  {Y : โ„• โ†’ ฮฉ โ†’ ๐“จ}
  (hA : โˆ€ (n : โ„•), Measurable (A n))
  (hY : โˆ€ (n : โ„•), Measurable (Y n)) :
  MeasureTheory.Filtration โ„• mฮฉ

Code

def IsAlgEnvSeq.filtration (hA : โˆ€ n, Measurable (A n)) (hY : โˆ€ n, Measurable (Y n)) :
    Filtration โ„• mฮฉ where
  seq i := MeasurableSpace.comap (history A Y i) inferInstance
  mono' i j hij := by
    simp only
    rw [โ† measurable_iff_comap_le]
    have : history A Y i = (fun h k โ†ฆ h โŸจk.1, by grindโŸฉ) โˆ˜ history A Y j := rfl
    rw [this]
    exact measurable_comp_comap _ (by fun_prop)
  le' i := by
    rw [โ† measurable_iff_comap_le]
    exact Learning.measurable_history hA hY i
Body uses (3)
Used by (18)

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stepsUntil๐Ÿ”—

DefinitionLearning.stepsUntil
Details

Number of steps until action a was pulled exactly m times.

๐Ÿ”—def
Learning.stepsUntil.{u_1, u_3} {๐“ : Type u_1} {ฮฉ : Type u_3}
  [DecidableEq ๐“] (A : โ„• โ†’ ฮฉ โ†’ ๐“) (a : ๐“) (m : โ„•) (ฯ‰ : ฮฉ) : โ„•โˆž
Learning.stepsUntil.{u_1, u_3}
  {๐“ : Type u_1} {ฮฉ : Type u_3}
  [DecidableEq ๐“] (A : โ„• โ†’ ฮฉ โ†’ ๐“) (a : ๐“)
  (m : โ„•) (ฯ‰ : ฮฉ) : โ„•โˆž

Code

noncomputable
def stepsUntil (A : โ„• โ†’ ฮฉ โ†’ ๐“) (a : ๐“) (m : โ„•) (ฯ‰ : ฮฉ) : โ„•โˆž :=
  sInf ((โ†‘) '' {s | pullCount A a (s + 1) ฯ‰ = m})
Body uses (1)
Used by (46)

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All dependencies, transitively (4)

history๐Ÿ”—

DefinitionLearning.history
Details

History of the algorithm-environment sequence up to time n.

๐Ÿ”—def
Learning.history.{u_1, u_2, u_3} {๐“ : Type u_1} {๐“จ : Type u_2}
  {ฮฉ : Type u_3} (A : โ„• โ†’ ฮฉ โ†’ ๐“) (Y : โ„• โ†’ ฮฉ โ†’ ๐“จ) (n : โ„•) (ฯ‰ : ฮฉ) :
  โ†ฅ(Finset.Iic n) โ†’ ๐“ ร— ๐“จ
Learning.history.{u_1, u_2, u_3}
  {๐“ : Type u_1} {๐“จ : Type u_2}
  {ฮฉ : Type u_3} (A : โ„• โ†’ ฮฉ โ†’ ๐“)
  (Y : โ„• โ†’ ฮฉ โ†’ ๐“จ) (n : โ„•) (ฯ‰ : ฮฉ) :
  โ†ฅ(Finset.Iic n) โ†’ ๐“ ร— ๐“จ

Code

def history (A : โ„• โ†’ ฮฉ โ†’ ๐“) (Y : โ„• โ†’ ฮฉ โ†’ ๐“จ) (n : โ„•) (ฯ‰ : ฮฉ) : Iic n โ†’ ๐“ ร— ๐“จ :=
  fun i โ†ฆ (A i ฯ‰, Y i ฯ‰)
Used by (72)

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measurable_comp_comap๐Ÿ”—

LemmaMeasureTheory.measurable_comp_comap
Details

No docstring.

๐Ÿ”—theorem
MeasureTheory.measurable_comp_comap.{u_1, u_2, u_3} {ฮฑ : Type u_1}
  {ฮฒ : Type u_2} {ฮณ : Type u_3} {mฮฒ : MeasurableSpace ฮฒ}
  {mฮณ : MeasurableSpace ฮณ} (f : ฮฑ โ†’ ฮฒ) {g : ฮฒ โ†’ ฮณ} (hg : Measurable g) :
  Measurable (g โˆ˜ f)
MeasureTheory.measurable_comp_comap.{u_1,
    u_2, u_3}
  {ฮฑ : Type u_1} {ฮฒ : Type u_2}
  {ฮณ : Type u_3} {mฮฒ : MeasurableSpace ฮฒ}
  {mฮณ : MeasurableSpace ฮณ} (f : ฮฑ โ†’ ฮฒ)
  {g : ฮฒ โ†’ ฮณ} (hg : Measurable g) :
  Measurable (g โˆ˜ f)

Code

lemma measurable_comp_comap (f : ฮฑ โ†’ ฮฒ) {g : ฮฒ โ†’ ฮณ} (hg : Measurable g) :
    Measurable[mฮฒ.comap f] (g โˆ˜ f)
Used by (10)

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Proof
by
  rw [measurable_iff_comap_le, โ† MeasurableSpace.comap_comp]
  exact MeasurableSpace.comap_mono hg.comap_le

measurable_history๐Ÿ”—

LemmaLearning.measurable_history
Details

No docstring.

๐Ÿ”—theorem
Learning.measurable_history.{u_1, u_2, u_3} {๐“ : Type u_1}
  {๐“จ : Type u_2} {ฮฉ : Type u_3} {m๐“ : MeasurableSpace ๐“}
  {m๐“จ : MeasurableSpace ๐“จ} {mฮฉ : MeasurableSpace ฮฉ} {A : โ„• โ†’ ฮฉ โ†’ ๐“}
  {Y : โ„• โ†’ ฮฉ โ†’ ๐“จ} (hA : โˆ€ (n : โ„•), Measurable (A n))
  (hY : โˆ€ (n : โ„•), Measurable (Y n)) (n : โ„•) :
  Measurable (history A Y n)
Learning.measurable_history.{u_1, u_2,
    u_3}
  {๐“ : Type u_1} {๐“จ : Type u_2}
  {ฮฉ : Type u_3} {m๐“ : MeasurableSpace ๐“}
  {m๐“จ : MeasurableSpace ๐“จ}
  {mฮฉ : MeasurableSpace ฮฉ} {A : โ„• โ†’ ฮฉ โ†’ ๐“}
  {Y : โ„• โ†’ ฮฉ โ†’ ๐“จ}
  (hA : โˆ€ (n : โ„•), Measurable (A n))
  (hY : โˆ€ (n : โ„•), Measurable (Y n))
  (n : โ„•) : Measurable (history A Y n)

Code

lemma measurable_history (hA : โˆ€ n, Measurable (A n))
    (hY : โˆ€ n, Measurable (Y n)) (n : โ„•) :
    Measurable (history A Y n)
Type uses (1)
Used by (10)

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Proof
by
  unfold history
  fun_prop

pullCount๐Ÿ”—

DefinitionLearning.pullCount
Details

Number of times action a was chosen up to time t (excluding t).

๐Ÿ”—def
Learning.pullCount.{u_1, u_3} {๐“ : Type u_1} {ฮฉ : Type u_3}
  [DecidableEq ๐“] (A : โ„• โ†’ ฮฉ โ†’ ๐“) (a : ๐“) (t : โ„•) (ฯ‰ : ฮฉ) : โ„•
Learning.pullCount.{u_1, u_3}
  {๐“ : Type u_1} {ฮฉ : Type u_3}
  [DecidableEq ๐“] (A : โ„• โ†’ ฮฉ โ†’ ๐“) (a : ๐“)
  (t : โ„•) (ฯ‰ : ฮฉ) : โ„•

Code

noncomputable
def pullCount (A : โ„• โ†’ ฮฉ โ†’ ๐“) (a : ๐“) (t : โ„•) (ฯ‰ : ฮฉ) : โ„• :=
  #(filter (fun s โ†ฆ A s ฯ‰ = a) (range t))
Used by (146)

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