{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T17:53:14Z","timestamp":1768413194283,"version":"3.49.0"},"reference-count":20,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"JST Moonshot R&amp;D, Japan","award":["JPMJMS2292"],"award-info":[{"award-number":["JPMJMS2292"]}]},{"name":"JST CREST","award":["JPMJCR21P4"],"award-info":[{"award-number":["JPMJCR21P4"]}]},{"name":"JSPS KAKENHI","award":["21H05053"],"award-info":[{"award-number":["21H05053"]}]},{"name":"World Premier International Research Center Initiative"},{"name":"JSPS KAKENHI","award":["JP90542217"],"award-info":[{"award-number":["JP90542217"]}]},{"name":"JSPS KAKENHI","award":["JPNP16007"],"award-info":[{"award-number":["JPNP16007"]}]},{"DOI":"10.13039\/501100001863","name":"New Energy and Industrial Technology Development Organization","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001863","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004410","name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004410","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004410","name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu","doi-asserted-by":"publisher","award":["118E923"],"award-info":[{"award-number":["118E923"]}],"id":[{"id":"10.13039\/501100004410","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Robot. Autom. Lett."],"published-print":{"date-parts":[[2024,5]]},"DOI":"10.1109\/lra.2024.3382534","type":"journal-article","created":{"date-parts":[[2024,3,27]],"date-time":"2024-03-27T19:35:18Z","timestamp":1711568118000},"page":"4463-4470","source":"Crossref","is-referenced-by-count":3,"title":["Correspondence Learning Between Morphologically Different Robots via Task Demonstrations"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-4796-4281","authenticated-orcid":false,"given":"Hakan","family":"Aktas","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, Bogazici University, Istanbul, T&#x00FC;rkiye"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4794-0940","authenticated-orcid":false,"given":"Yukie","family":"Nagai","sequence":"additional","affiliation":[{"name":"IRCN, The University of Tokyo, Tokyo, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9506-6333","authenticated-orcid":false,"given":"Minoru","family":"Asada","sequence":"additional","affiliation":[{"name":"OTRI, SISREC, Osaka University, Osaka, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3051-6038","authenticated-orcid":false,"given":"Erhan","family":"Oztop","sequence":"additional","affiliation":[{"name":"OTRI, SISREC, Osaka University, Osaka, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9597-2731","authenticated-orcid":false,"given":"Emre","family":"Ugur","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Bogazici University, Istanbul, T&#x00FC;rkiye"}]}],"member":"263","reference":[{"issue":"7","key":"ref1","first-page":"1633","article-title":"Transfer learning for reinforcement learning domains: A survey","volume":"10","author":"Taylor","year":"2009","journal-title":"J. Mach. Learn. Res."},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-87481-2_32"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-28499-1_2"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9631"},{"key":"ref5","article-title":"State alignment-based imitation learning","author":"Liu","year":"2019"},{"key":"ref6","article-title":"Learning invariant feature spaces to transfer skills with reinforcement learning","author":"Gupta","year":"2017"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989250"},{"key":"ref8","first-page":"4159","article-title":"Hierarchically decoupled imitation for morphological transfer","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Hejna","year":"2020"},{"key":"ref9","article-title":"Third-person visual imitation learning via decoupled hierarchical controller","volume-title":"Proc. 33rd Int. Conf. Neural Inf. Process. Syst.","author":"Sharma","year":"2019"},{"key":"ref10","article-title":"Learning cross-domain correspondence for control with dynamics cycle-consistency","author":"Zhang","year":"2020"},{"key":"ref11","first-page":"5286","article-title":"Domain adaptive imitation learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Kim","year":"2020"},{"key":"ref12","first-page":"1896","article-title":"ACNMP: Skill transfer and task extrapolation through learning from demonstration and reinforcement learning via representation sharing","volume-title":"Proc. Conf. Robot Learn.","author":"Akbulut","year":"2021"},{"key":"ref13","article-title":"Open X-embodiment: Robotic learning datasets and RT-X models","author":"Padalkar","year":"2023"},{"key":"ref14","article-title":"RoboCat: A self-improving foundation agent for robotic manipulation","author":"Bousmalis","year":"2023"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2021.11.004"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2019.XV.071"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1080\/01691864.2023.2225232"},{"issue":"1","key":"ref18","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2013.6696520"},{"key":"ref20","article-title":"Affordances as a framework for robot control","volume-title":"Proc. 7th Int. Conf. Epigenetic Robot.","author":"Cakmak","year":"2007"}],"container-title":["IEEE Robotics and Automation Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7083369\/10474437\/10480569.pdf?arnumber=10480569","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,23]],"date-time":"2024-12-23T19:30:23Z","timestamp":1734982223000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10480569\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5]]},"references-count":20,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/lra.2024.3382534","relation":{},"ISSN":["2377-3766","2377-3774"],"issn-type":[{"value":"2377-3766","type":"electronic"},{"value":"2377-3774","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5]]}}}