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dc.contributor.authorSilver, Tom
dc.contributor.authorChitnis, Rohan
dc.contributor.authorTenenbaum, Joshua
dc.contributor.authorKaelbling, Leslie Pack
dc.contributor.authorLozano-Perez, Tomas
dc.date.accessioned2022-07-14T19:14:36Z
dc.date.available2022-07-14T19:14:36Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/1721.1/143745
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionof10.1109/IROS51168.2021.9635941en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcearXiven_US
dc.titleLearning Symbolic Operators for Task and Motion Planningen_US
dc.typeArticleen_US
dc.identifier.citationSilver, Tom, Chitnis, Rohan, Tenenbaum, Joshua, Kaelbling, Leslie Pack and Lozano-Perez, Tomas. 2021. "Learning Symbolic Operators for Task and Motion Planning." 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.relation.journal2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)en_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2022-07-14T19:10:32Z
dspace.orderedauthorsSilver, T; Chitnis, R; Tenenbaum, J; Kaelbling, LP; Lozano-Perez, Ten_US
dspace.date.submission2022-07-14T19:10:33Z
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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