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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