Optimal stroke learning with policy gradient approach for robotic table tennis

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dc.contributor.author Gao, Yapeng
dc.contributor.author Tebbe, Jonas
dc.contributor.author Zell, Andreas
dc.date.accessioned 2023-10-11T09:13:37Z
dc.date.available 2023-10-11T09:13:37Z
dc.date.issued 2022-10-08
dc.identifier.issn 0924-669X
dc.identifier.uri http://hdl.handle.net/10900/146138
dc.language.iso en de_DE
dc.publisher Springer Link de_DE
dc.relation.uri http://dx.doi.org/10.1007/s10489-022-04131-w de_DE
dc.subject.ddc 004 de_DE
dc.title Optimal stroke learning with policy gradient approach for robotic table tennis de_DE
dc.type Article de_DE
utue.quellen.id 20230619000000_02021
utue.publikation.seiten 13309-13322 de_DE
utue.personen.roh Gao, Yapeng
utue.personen.roh Tebbe, Jonas
utue.personen.roh Zell, Andreas
dcterms.isPartOf.ZSTitelID Applied Intelligence de_DE
dcterms.isPartOf.ZS-Issue 11 de_DE
dcterms.isPartOf.ZS-Volume 53 de_DE
utue.fakultaet 07 Mathematisch-Naturwissenschaftliche Fakultät de_DE


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