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Article: Learning to Delay in Ride-Sourcing Systems: A Multi-Agent Deep Reinforcement Learning Framework

TitleLearning to Delay in Ride-Sourcing Systems: A Multi-Agent Deep Reinforcement Learning Framework
Authors
Ke, JXiao, FYang, HYe, J
Issue Date2022
Citation
IEEE Transactions on Knowledge and Data Engineering, 2022, v. 34, p. 2280-2292 How to Cite?
DOI: http://dx.doi.org/10.1109/TKDE.2020.3006084
Persistent Identifierhttp://hdl.handle.net/10722/321173
ISI Accession Number ID
WOS:000777332000020

 

DC FieldValueLanguage
dc.contributor.authorKe, J-
dc.contributor.authorXiao, F-
dc.contributor.authorYang, H-
dc.contributor.authorYe, J-
dc.date.accessioned2022-11-01T04:48:16Z-
dc.date.available2022-11-01T04:48:16Z-
dc.date.issued2022-
dc.identifier.citationIEEE Transactions on Knowledge and Data Engineering, 2022, v. 34, p. 2280-2292-
dc.identifier.urihttp://hdl.handle.net/10722/321173-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Knowledge and Data Engineering-
dc.titleLearning to Delay in Ride-Sourcing Systems: A Multi-Agent Deep Reinforcement Learning Framework-
dc.typeArticle-
dc.identifier.emailKe, J: kejintao@hku.hk-
dc.identifier.authorityKe, J=rp02901-
dc.identifier.doi10.1109/TKDE.2020.3006084-
dc.identifier.hkuros340772-
dc.identifier.volume34-
dc.identifier.spage2280-
dc.identifier.epage2292-
dc.identifier.isiWOS:000777332000020-

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