BanditRLlib
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Lean module · Foundations

BanditRLProof.Algorithms.MOSSHistory

An inclusive history at t contains t+1 observations; the successor selector therefore calls the source action at t+1. No reward law or concentration certificate is required to construct this deterministic Markov policy.

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Declarations
6
Placeholders
0

Imports

BanditRLProof.Algorithms.MOSS, BanditRLProof.Algorithms.UCBRealHistoryIndex, BanditRLProof.Algorithms.ThompsonAlgorithmDensityProcess

Imported by

BanditRLProof, BanditRLProof.Algorithms.MOSSStreamMeasurable

Declarations

Open an item to read its exact compact statement and source link. Detailed teaching notes are linked when registered.

def BanditRLProof.MOSS.historyAction Compiled

Source MOSS action after an inclusive finite action/reward history.

Used in these reading views: Bandit Book

1. Finite bandits, traces, and regret

Canonical node identitydeclaration:BanditRLProof.MOSS.historyAction

Reading membership is not a proof dependency. Exact assumptions remain in the Lean statement.

noncomputable def historyAction {k : ℕ} (hk : 0 < k) (n t : ℕ) (history : History.FinitePairHistory (Fin k) ℝ t) : Fin k
theorem BanditRLProof.MOSS.measurable_historyAction Compiled

No declaration docstring is present; use the chapter context and exact statement below.

Used in these reading views: Bandit Book

1. Finite bandits, traces, and regret

Canonical node identitydeclaration:BanditRLProof.MOSS.measurable_historyAction

Reading membership is not a proof dependency. Exact assumptions remain in the Lean statement.

theorem measurable_historyAction {k : ℕ} (hk : 0 < k) (n t : ℕ) : Measurable (historyAction hk n t)
def BanditRLProof.MOSS.historyAlgorithm Compiled

Concrete MOSS policy on the history interface shared by Chapter 13's minimax regret functional. Initial action is arm zero.

Used in these reading views: Bandit Book

1. Finite bandits, traces, and regret · Chapter 13: Lower Bounds: Basic Ideas

Canonical node identitydeclaration:BanditRLProof.MOSS.historyAlgorithm

Reading membership is not a proof dependency. Exact assumptions remain in the Lean statement.

noncomputable def historyAlgorithm {k : ℕ} (hk : 0 < k) (n : ℕ) : Thompson.HistoryAlgorithm (Fin k) ℝ where
theorem BanditRLProof.MOSS.historyAlgorithm_policy_apply Compiled

No declaration docstring is present; use the chapter context and exact statement below.

Used in these reading views: Bandit Book

1. Finite bandits, traces, and regret

Canonical node identitydeclaration:BanditRLProof.MOSS.historyAlgorithm_policy_apply

Reading membership is not a proof dependency. Exact assumptions remain in the Lean statement.

@[simp] theorem historyAlgorithm_policy_apply {k : ℕ} (hk : 0 < k) (n t : ℕ) (history : History.FinitePairHistory (Fin k) ℝ t) : (historyAlgorithm hk n).policy t history = Measure.dirac (historyAction hk n t history)
theorem BanditRLProof.MOSS.historyAction_initialization Compiled

Subsequent initialization rounds select the corresponding arm.

Used in these reading views: Bandit Book

1. Finite bandits, traces, and regret

Canonical node identitydeclaration:BanditRLProof.MOSS.historyAction_initialization

Reading membership is not a proof dependency. Exact assumptions remain in the Lean statement.

theorem historyAction_initialization {k : ℕ} (hk : 0 < k) (n t : ℕ) (history : History.FinitePairHistory (Fin k) ℝ t) (ht : t + 1 < k) : historyAction hk n t history = ⟨t + 1, ht⟩
theorem BanditRLProof.MOSS.historyAction_index_max Compiled

Exact post-initialization source index maximality on visible history.

Used in these reading views: Bandit Book

1. Finite bandits, traces, and regret

Canonical node identitydeclaration:BanditRLProof.MOSS.historyAction_index_max

Reading membership is not a proof dependency. Exact assumptions remain in the Lean statement.

theorem historyAction_index_max {k : ℕ} (hk : 0 < k) (n t : ℕ) (history : History.FinitePairHistory (Fin k) ℝ t) (ht : k ≤ t + 1) (a : Fin k) : index n (ETC.realHistoryEmpMean t history) (ETC.realHistoryPullCount t history) a ≤ index n (ETC.realHistoryEmpMean t history) (ETC.realHistoryPullCount t history) (historyAction hk n t history)