A model-based bootstrap achieves distributional consistency for transition estimators in controlled Markov chains with unknown policies and yields asymptotically valid confidence intervals for offline policy evaluation and optimal policy recovery.
[2025, Lemma 3] then implies that Assumption 2 holds for the bootstrap CMC, and∥∆∗ n∥ ≤0+ 2C∗ρ∗ 1−ρ∗ +1 = C ∗ ∆ for alln≥N 0 a.s
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ML 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Model-based Bootstrap of Controlled Markov Chains
A model-based bootstrap achieves distributional consistency for transition estimators in controlled Markov chains with unknown policies and yields asymptotically valid confidence intervals for offline policy evaluation and optimal policy recovery.