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LeanMachineLearning.SequentialLearning.Algorithms.RandomSampling

Random Sampling #

Implementation of the Random Sampling algorithm, which samples from a fixed probability measure at each iteration.

Main definitions #

Main statements #

noncomputable def Learning.randomSampling {𝓐 : Type u_1} {𝓨 : Type u_2} [MeasurableSpace 𝓐] [MeasurableSpace 𝓨] (ΞΌ : MeasureTheory.Measure 𝓐) [MeasureTheory.IsProbabilityMeasure ΞΌ] :
Algorithm 𝓐 𝓨

The Random Sampling algorithm, which samples from a fixed probability measure at each iteration.

Equations
Instances For
    @[simp]
    theorem Learning.randomSampling_p0 {𝓐 : Type u_1} {𝓨 : Type u_2} [MeasurableSpace 𝓐] [MeasurableSpace 𝓨] (ΞΌ : MeasureTheory.Measure 𝓐) [MeasureTheory.IsProbabilityMeasure ΞΌ] :
    (randomSampling ΞΌ).p0 = ΞΌ
    @[simp]
    theorem Learning.randomSampling_policy {𝓐 : Type u_1} {𝓨 : Type u_2} [MeasurableSpace 𝓐] [MeasurableSpace 𝓨] (ΞΌ : MeasureTheory.Measure 𝓐) [MeasureTheory.IsProbabilityMeasure ΞΌ] (x✝ : β„•) :
    (randomSampling ΞΌ).policy x✝ = ProbabilityTheory.Kernel.const (β†₯(Finset.Iic x✝) β†’ 𝓐 Γ— 𝓨) ΞΌ
    theorem Learning.randomSampling.hasLaw_action {𝓐 : Type u_1} {𝓨 : Type u_2} {Ξ© : Type u_3} [MeasurableSpace 𝓐] [MeasurableSpace 𝓨] [StandardBorelSpace 𝓐] [Nonempty 𝓐] [StandardBorelSpace 𝓨] [Nonempty 𝓨] {ΞΌ : MeasureTheory.Measure 𝓐} [MeasureTheory.IsProbabilityMeasure ΞΌ] [MeasurableSpace Ξ©] {P : MeasureTheory.Measure Ξ©} [MeasureTheory.IsProbabilityMeasure P] {A : β„• β†’ Ξ© β†’ 𝓐} {Y : β„• β†’ Ξ© β†’ 𝓨} {env : Environment 𝓐 𝓨} (h : IsAlgEnvSeq A Y (randomSampling ΞΌ) env P) (n : β„•) :

    Each action follows the distribution ΞΌ.

    theorem Learning.randomSampling.iIndep_action {𝓐 : Type u_1} {𝓨 : Type u_2} {Ξ© : Type u_3} [MeasurableSpace 𝓐] [MeasurableSpace 𝓨] [StandardBorelSpace 𝓐] [Nonempty 𝓐] [StandardBorelSpace 𝓨] [Nonempty 𝓨] {ΞΌ : MeasureTheory.Measure 𝓐} [MeasureTheory.IsProbabilityMeasure ΞΌ] [MeasurableSpace Ξ©] {P : MeasureTheory.Measure Ξ©} [MeasureTheory.IsProbabilityMeasure P] {A : β„• β†’ Ξ© β†’ 𝓐} {Y : β„• β†’ Ξ© β†’ 𝓨} {env : Environment 𝓐 𝓨} (h : IsAlgEnvSeq A Y (randomSampling ΞΌ) env P) :

    Actions are mutually independent.