Optimal stroke learning with policy gradient approach for robotic table tennis

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dc.contributor.author Zell, Andreas
dc.contributor.author Tebbe, Jonas
dc.contributor.author Gao, Yapeng
dc.date.accessioned 2023-07-07T09:43:04Z
dc.date.available 2023-07-07T09:43:04Z
dc.date.issued 2022-10-08
dc.identifier.uri http://hdl.handle.net/10900/143224
dc.language.iso en de_DE
dc.publisher Springer Link de_DE
dc.relation.uri https://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.publikation.seiten 13309–13322 de_DE
utue.personen.roh Zell, Andreas
utue.personen.roh Tebbe, Jonas
utue.personen.roh Gao, Yapeng
dcterms.isPartOf.ZSTitelID Applied Intelligence de_DE
dcterms.isPartOf.ZS-Volume 53 de_DE


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