An asymptotically optimal heuristic for general nonstationary finite-horizon restless multi-armed, multi-action bandits: Corrigendum

Pub Date : 2023-03-22 DOI:10.1017/apr.2022.59
Gabriel Zayas-Cabán, Jiaxin Liang, Stefanus Jasin, Guihua Wang
{"title":"An asymptotically optimal heuristic for general nonstationary finite-horizon restless multi-armed, multi-action bandits: Corrigendum","authors":"Gabriel Zayas-Cabán, Jiaxin Liang, Stefanus Jasin, Guihua Wang","doi":"10.1017/apr.2022.59","DOIUrl":null,"url":null,"abstract":"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:","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1017/apr.2022.59","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

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:
分享
查看原文
一般非平稳有限域不安多武装多行动土匪的渐近最优启发式算法:勘误表
上述引理用于证明[1]第4节和第6节中的定理1 - 2和命题1 - 3。有人慷慨地向我们指出,引理中的界通常可能是不正确的。该引理的原始证明使用了线性规划对偶和灵敏度分析结果的组合。错误在于在一定的假设下应用已知的灵敏度分析结果,而我们的LP不一定满足。幸运的是,上面引理中的界是可以修正的。我们将在这个更正注中证明的新界如下:
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信