{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T14:25:25Z","timestamp":1779287125671,"version":"3.51.4"},"reference-count":61,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,5,19]],"date-time":"2025-05-19T00:00:00Z","timestamp":1747612800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,5,19]],"date-time":"2025-05-19T00:00:00Z","timestamp":1747612800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,5,19]]},"DOI":"10.1109\/icra55743.2025.11127692","type":"proceedings-article","created":{"date-parts":[[2025,9,2]],"date-time":"2025-09-02T17:28:56Z","timestamp":1756834136000},"page":"6519-6526","source":"Crossref","is-referenced-by-count":3,"title":["Neuro-Symbolic Imitation Learning: Discovering Symbolic Abstractions for Skill Learning"],"prefix":"10.1109","author":[{"given":"Leon","family":"Keller","sequence":"first","affiliation":[{"name":"Intelligent Autonomous Systems,TU Darmstadt,Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel","family":"Tanneberg","sequence":"additional","affiliation":[{"name":"Honda Research Institute EU,Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jan","family":"Peters","sequence":"additional","affiliation":[{"name":"Intelligent Autonomous Systems,TU Darmstadt,Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3213246"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/s41315-019-00103-5"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2024.3395626"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1561\/9781680834116"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-19457-3_28"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2014.6943187"},{"key":"ref7","article-title":"Taco: Learning task decomposition via temporal alignment for control","volume-title":"International Conference on Machine Learning","author":"Shiarlis"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3068891"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1126\/science.1192788"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.cobeha.2018.11.005"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-020-00255-1"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-control-091420-084139"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3583136"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.3389\/frobt.2021.637888"},{"key":"ref15","article-title":"Learning grounded relational symbols from continuous data for abstract reasoning","volume-title":"Proceedings of the 2013 ICRA Workshop on Autonomous Learning","author":"Jetchev"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.3233\/FAIA200361"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.24963\/kr.2021\/51"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1613\/jair.5575"},{"key":"ref19","article-title":"Active exploration for learning symbolic representations","volume":"30","author":"Andersen","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref20","article-title":"Symbol acquisition for probabilistic high-level planning","volume-title":"AAAI Press\/International Joint Conferences on Artificial Intelligence","author":"Konidaris"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v28i1.9004"},{"key":"ref22","first-page":"4682","article-title":"Learning portable representations for high-level planning","volume-title":"International Conference on Machine Learning. PMLR","author":"James"},{"key":"ref23","article-title":"Autonomous learning of object-centric abstractions for highlevel planning","volume-title":"International Conference on Learning Representations","author":"James"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1613\/jair.1.13754"},{"key":"ref25","article-title":"Learning multi-object symbols for manipulation with attentive deep effect predictors","author":"Ahmetoglu","year":"2022","journal-title":"arXiv preprint"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2024.3350994"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1613\/jair.1.13768"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1609\/icaps.v29i1.3525"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i6.16627"},{"key":"ref30","article-title":"Learning a symbolic planning domain through the interaction with continuous environments","author":"Umili","year":"2021","journal-title":"in ICAPS PRL Workshop"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i10.26429"},{"key":"ref32","first-page":"2193","article-title":"Discovering a symbolic planning language from continuous experience","author":"Loula","year":"2019","journal-title":"in CogSci"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1613\/jair.2113"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i5.20475"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/IROS55552.2023.10342301"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TAI.2023.3311428"},{"key":"ref37","first-page":"7949","article-title":"Leveraging approximate symbolic models for reinforcement learning via skill diversity","volume-title":"International Conference on Machine Learning. PMLR","author":"Guan"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33012970"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1609\/icaps.v31i1.16001"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/675"},{"key":"ref41","first-page":"arXiv","article-title":"Creativity of ai: Hierarchical planning model learning for facilitating deep reinforcement learning","author":"Zhuo","year":"2021","journal-title":"arXiv e-prints"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1609\/icaps.v30i1.6750"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-77949-0_6"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2023.3308061"},{"key":"ref45","article-title":"Learning neuro-symbolic skills for bilevel planning","author":"Silver","year":"2022","journal-title":"arXiv preprint"},{"key":"ref46","first-page":"3030","article-title":"Human-in-the-loop task and motion planning for imitation learning","volume-title":"Conference on Robot Learning. PMLR","author":"Mandlekar"},{"key":"ref47","first-page":"630","article-title":"Guided imitation of task and motion planning","volume-title":"Conference on Robot Learning. PMLR","author":"McDonald"},{"key":"ref48","article-title":"Pddl- the planning domain definition language","author":"Aeronautiques","year":"1998","journal-title":"Technical Report"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1613\/jair.1705"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1609\/socs.v16i1.27281"},{"key":"ref51","article-title":"Efficient symbolic planning with views","author":"Hasler","year":"2024","journal-title":"arXiv"},{"key":"ref52","article-title":"From reals to logic and back: Inventing symbolic vocabularies, actions and models for planning from raw data","author":"Shah","year":"2024","journal-title":"arXiv preprint"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/IROS47612.2022.9981440"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(94)90062-0"},{"issue":"8","key":"ref55","article-title":"Binary codes capable of correcting deletions, insertions, and reversals","volume":"10","author":"Levenshein","year":"1966","journal-title":"in Soviet Physics-Doklady"},{"key":"ref56","author":"Miller","year":"2009","journal-title":"Levenshtein distance"},{"key":"ref57","article-title":"Learning planning operators by observation and practice","volume-title":"Ph.D. dissertation","author":"Wang","year":"1996"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/615"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.24963\/kr.2022\/36"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2012.6386109"},{"key":"ref61","article-title":"robosuite: A modular simulation framework and benchmark for robot learning","author":"Zhu","year":"2020","journal-title":"arXiv preprint"}],"event":{"name":"2025 IEEE International Conference on Robotics and Automation (ICRA)","location":"Atlanta, GA, USA","start":{"date-parts":[[2025,5,19]]},"end":{"date-parts":[[2025,5,23]]}},"container-title":["2025 IEEE International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11127273\/11127223\/11127692.pdf?arnumber=11127692","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T06:05:33Z","timestamp":1756879533000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11127692\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,19]]},"references-count":61,"URL":"https:\/\/doi.org\/10.1109\/icra55743.2025.11127692","relation":{},"subject":[],"published":{"date-parts":[[2025,5,19]]}}}