Best Arm Identification in Restless Markov Multi-Armed Bandits-Reference-Cited by-同舟云学术

Best Arm Identification in Restless Markov Multi-Armed Bandits

Author:

Karthik P. N.¹^ORCID,Reddy Kota Srinivas²^ORCID,Tan Vincent Y. F.³^ORCID

Affiliation:

1. Institute of Data Science, National University of Singapore, Queenstown, Singapore

2. Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore

3. Department of Mathematics and the Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore

Funder

National Research Foundation (NRF) Singapore and DSO National Laboratories through the AI Singapore Program

NRF Fellowship

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Library and Information Sciences,Computer Science Applications,Information Systems

Link

Reference35 articles.

1. The sample complexity of exploration in the multi-armed bandit problem;mannor;J Mach Learn Res,2004

5. Almost optimal exploration in multi-armed bandits;karnin;Proc Int Conf Mach Learn,2013

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

2. Best Restless Markov Arm Identification;2022 IEEE Information Theory Workshop (ITW);2022-11-01