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dc.contributor.authorYu, Tiancheng
dc.contributor.authorTian, Yi
dc.contributor.authorZhang, Jingzhao
dc.contributor.authorSra, Suvrit
dc.date.accessioned2022-07-20T16:46:36Z
dc.date.available2022-07-20T16:46:36Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/1721.1/143897
dc.language.isoen
dc.relation.isversionofhttps://proceedings.mlr.press/v139/yu21b.htmlen_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceProceedings of Machine Learning Researchen_US
dc.titleProvably Efficient Algorithms for Multi-Objective Competitive RLen_US
dc.typeArticleen_US
dc.identifier.citationYu, Tiancheng, Tian, Yi, Zhang, Jingzhao and Sra, Suvrit. 2021. "Provably Efficient Algorithms for Multi-Objective Competitive RL." INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 139, 139.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.relation.journalINTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 139en_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2022-07-20T16:44:18Z
dspace.orderedauthorsYu, T; Tian, Y; Zhang, J; Sra, Sen_US
dspace.date.submission2022-07-20T16:44:19Z
mit.journal.volume139en_US
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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