Gabriel Zayas-Cabán, Jiaxin Liang, Stefanus Jasin, Guihua Wang
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An asymptotically optimal heuristic for general nonstationary finite-horizon restless multi-armed, multi-action bandits: Corrigendum
The above lemma is used to prove Theorems 1–2 and Propositions 1–3 in Sections 4 and 6 of [1]. It has been graciously pointed out to us that the bound in the lemma may not be correct in general. The original proof of this lemma uses a combination of linear program (LP) duality and sensitivity analysis results. The mistake is in the application of a known sensitivity analysis result under a certain assumption that happens to be not necessarily satisfied by our LP. Fortunately, it is possible to correct the bound in the above lemma. The new bound that we will prove in this correction note is as follows:
期刊介绍：
The Advances in Applied Probability has been published by the Applied Probability Trust for over four decades, and is a companion publication to the Journal of Applied Probability. It contains mathematical and scientific papers of interest to applied probabilists, with emphasis on applications in a broad spectrum of disciplines, including the biosciences, operations research, telecommunications, computer science, engineering, epidemiology, financial mathematics, the physical and social sciences, and any field where stochastic modeling is used.
A submission to Applied Probability represents a submission that may, at the Editor-in-Chief’s discretion, appear in either the Journal of Applied Probability or the Advances in Applied Probability. Typically, shorter papers appear in the Journal, with longer contributions appearing in the Advances.
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