Optimal stroke learning with policy gradient approach for robotic table tennis

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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