Bandits.regret_eq_sum_gap
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regret_eq_sum_gap🔗
Bandits.regret_eq_sum_gapNo docstring.
Bandits.regret_eq_sum_gap.{u_1, u_2} {𝓐 : Type u_1} {Ω : Type u_2} {m𝓐 : MeasurableSpace 𝓐} {ν : ProbabilityTheory.Kernel 𝓐 ℝ} {A : ℕ → Ω → 𝓐} {ω : Ω} {t : ℕ} : regret ν A t ω = ∑ s ∈ Finset.range t, gap ν (A s ω)Bandits.regret_eq_sum_gap.{u_1, u_2} {𝓐 : Type u_1} {Ω : Type u_2} {m𝓐 : MeasurableSpace 𝓐} {ν : ProbabilityTheory.Kernel 𝓐 ℝ} {A : ℕ → Ω → 𝓐} {ω : Ω} {t : ℕ} : regret ν A t ω = ∑ s ∈ Finset.range t, gap ν (A s ω)
Code
lemma regret_eq_sum_gap : regret ν A t ω = ∑ s ∈ range t, gap ν (A s ω)
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Proof
by simp [regret, gap]
Dependency graph
Type dependencies (2)
regret🔗
Bandits.regret
Regret of a sequence of pulls k : ℕ → 𝓐 at time t for the reward kernel ν ; Kernel 𝓐 ℝ.
Bandits.regret.{u_1, u_2} {𝓐 : Type u_1} {Ω : Type u_2} {m𝓐 : MeasurableSpace 𝓐} (ν : ProbabilityTheory.Kernel 𝓐 ℝ) (A : ℕ → Ω → 𝓐) (t : ℕ) (ω : Ω) : ℝBandits.regret.{u_1, u_2} {𝓐 : Type u_1} {Ω : Type u_2} {m𝓐 : MeasurableSpace 𝓐} (ν : ProbabilityTheory.Kernel 𝓐 ℝ) (A : ℕ → Ω → 𝓐) (t : ℕ) (ω : Ω) : ℝ
Code
noncomputable def regret (ν : Kernel 𝓐 ℝ) (A : ℕ → Ω → 𝓐) (t : ℕ) (ω : Ω) : ℝ := t * (⨆ a, (ν a)[id]) - ∑ s ∈ range t, (ν (A s ω))[id]
Used by (11)
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gap🔗
Bandits.gap
Gap of an action a: difference between the highest mean of the actions and the mean of a.
Bandits.gap.{u_1} {𝓐 : Type u_1} {m𝓐 : MeasurableSpace 𝓐} (ν : ProbabilityTheory.Kernel 𝓐 ℝ) (a : 𝓐) : ℝBandits.gap.{u_1} {𝓐 : Type u_1} {m𝓐 : MeasurableSpace 𝓐} (ν : ProbabilityTheory.Kernel 𝓐 ℝ) (a : 𝓐) : ℝ
Code
noncomputable def gap (ν : Kernel 𝓐 ℝ) (a : 𝓐) : ℝ := (⨆ i, (ν i)[id]) - (ν a)[id]
Used by (27)
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