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Article: A deep inverse reinforcement learning approach to route choice modeling with context-dependent rewards

TitleA deep inverse reinforcement learning approach to route choice modeling with context-dependent rewards
Authors
Zhao, ZLIANG, Y
Issue Date2023
Citation
Transportation Research Part C: Emerging Technologies, 2023, v. 149, p. 104079 How to Cite?
DOI: http://dx.doi.org/10.1016/j.trc.2023.104079
Persistent Identifierhttp://hdl.handle.net/10722/326000
ISI Accession Number ID
WOS:000997648000001

 

DC FieldValueLanguage
dc.contributor.authorZhao, Z-
dc.contributor.authorLIANG, Y-
dc.date.accessioned2023-03-06T01:28:43Z-
dc.date.available2023-03-06T01:28:43Z-
dc.date.issued2023-
dc.identifier.citationTransportation Research Part C: Emerging Technologies, 2023, v. 149, p. 104079-
dc.identifier.urihttp://hdl.handle.net/10722/326000-
dc.languageeng-
dc.relation.ispartofTransportation Research Part C: Emerging Technologies-
dc.titleA deep inverse reinforcement learning approach to route choice modeling with context-dependent rewards-
dc.typeArticle-
dc.identifier.emailZhao, Z: zhanzhao@hku.hk-
dc.identifier.authorityZhao, Z=rp02712-
dc.identifier.doi10.1016/j.trc.2023.104079-
dc.identifier.hkuros344393-
dc.identifier.volume149-
dc.identifier.spage104079-
dc.identifier.epage104079-
dc.identifier.isiWOS:000997648000001-

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