Learning.isPredictable_pullCount
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isPredictable_pullCount๐
Learning.isPredictable_pullCountNo docstring.
Learning.isPredictable_pullCount.{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} [MeasurableSingletonClass ๐] (hA : โ (n : โ), Measurable (A n)) (hR' : โ (n : โ), Measurable (R' n)) (a : ๐) : MeasureTheory.IsStronglyPredictable (IsAlgEnvSeq.filtration hA hR') (pullCount A a)Learning.isPredictable_pullCount.{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} [MeasurableSingletonClass ๐] (hA : โ (n : โ), Measurable (A n)) (hR' : โ (n : โ), Measurable (R' n)) (a : ๐) : MeasureTheory.IsStronglyPredictable (IsAlgEnvSeq.filtration hA hR') (pullCount A a)
Code
lemma isPredictable_pullCount [MeasurableSingletonClass ๐]
(hA : โ n, Measurable (A n)) (hR' : โ n, Measurable (R' n)) (a : ๐) :
IsStronglyPredictable (IsAlgEnvSeq.filtration hA hR') (pullCount A a)Type uses (2)
Body uses (2)
Used by (1)
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Proof
by rw [IsStronglyPredictable.iff_measurable_add_one] refine โจ?_, stronglyAdapted_pullCount_add_one hA hR' aโฉ simp only [pullCount_zero] fun_prop
Dependency graph
Type dependencies (2)
filtration๐
Learning.IsAlgEnvSeq.filtration
Filtration generated by the history up to time n.
Learning.IsAlgEnvSeq.filtration.{u_1, u_2, u_3} {๐ : Type u_1} {๐จ : Type u_2} {ฮฉ : Type u_3} {m๐ : MeasurableSpace ๐} {m๐จ : MeasurableSpace ๐จ} {mฮฉ : MeasurableSpace ฮฉ} {A : โ โ ฮฉ โ ๐} {Y : โ โ ฮฉ โ ๐จ} (hA : โ (n : โ), Measurable (A n)) (hY : โ (n : โ), Measurable (Y n)) : MeasureTheory.Filtration โ mฮฉLearning.IsAlgEnvSeq.filtration.{u_1, u_2, u_3} {๐ : Type u_1} {๐จ : Type u_2} {ฮฉ : Type u_3} {m๐ : MeasurableSpace ๐} {m๐จ : MeasurableSpace ๐จ} {mฮฉ : MeasurableSpace ฮฉ} {A : โ โ ฮฉ โ ๐} {Y : โ โ ฮฉ โ ๐จ} (hA : โ (n : โ), Measurable (A n)) (hY : โ (n : โ), Measurable (Y n)) : MeasureTheory.Filtration โ mฮฉ
Code
def IsAlgEnvSeq.filtration (hA : โ n, Measurable (A n)) (hY : โ 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 โฆ h โจk.1, by grindโฉ) โ 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 iBody uses (3)
Used by (18)
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pullCount๐
Learning.pullCount
Number of times action a was chosen up to time t (excluding t).
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) : โLearning.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 โฆ A s ฯ = a) (range t))
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All dependencies, transitively (3)
history๐
Learning.history
History of the algorithm-environment sequence up to time n.
Learning.history.{u_1, u_2, u_3} {๐ : Type u_1} {๐จ : Type u_2} {ฮฉ : Type u_3} (A : โ โ ฮฉ โ ๐) (Y : โ โ ฮฉ โ ๐จ) (n : โ) (ฯ : ฮฉ) : โฅ(Finset.Iic n) โ ๐ ร ๐จLearning.history.{u_1, u_2, u_3} {๐ : Type u_1} {๐จ : Type u_2} {ฮฉ : Type u_3} (A : โ โ ฮฉ โ ๐) (Y : โ โ ฮฉ โ ๐จ) (n : โ) (ฯ : ฮฉ) : โฅ(Finset.Iic n) โ ๐ ร ๐จ
Code
def history (A : โ โ ฮฉ โ ๐) (Y : โ โ ฮฉ โ ๐จ) (n : โ) (ฯ : ฮฉ) : Iic n โ ๐ ร ๐จ := fun i โฆ (A i ฯ, Y i ฯ)
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measurable_comp_comap๐
MeasureTheory.measurable_comp_comapNo docstring.
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 โ 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 โ f)
Code
lemma measurable_comp_comap (f : ฮฑ โ ฮฒ) {g : ฮฒ โ ฮณ} (hg : Measurable g) :
Measurable[mฮฒ.comap f] (g โ 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_history๐
Learning.measurable_historyNo docstring.
Learning.measurable_history.{u_1, u_2, u_3} {๐ : Type u_1} {๐จ : Type u_2} {ฮฉ : Type u_3} {m๐ : MeasurableSpace ๐} {m๐จ : MeasurableSpace ๐จ} {mฮฉ : MeasurableSpace ฮฉ} {A : โ โ ฮฉ โ ๐} {Y : โ โ ฮฉ โ ๐จ} (hA : โ (n : โ), Measurable (A n)) (hY : โ (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} {๐จ : Type u_2} {ฮฉ : Type u_3} {m๐ : MeasurableSpace ๐} {m๐จ : MeasurableSpace ๐จ} {mฮฉ : MeasurableSpace ฮฉ} {A : โ โ ฮฉ โ ๐} {Y : โ โ ฮฉ โ ๐จ} (hA : โ (n : โ), Measurable (A n)) (hY : โ (n : โ), Measurable (Y n)) (n : โ) : Measurable (history A Y n)
Code
lemma measurable_history (hA : โ n, Measurable (A n))
(hY : โ 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