{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T19:11:40Z","timestamp":1763579500792,"version":"3.45.0"},"reference-count":23,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"euROBIN"},{"name":"ERC SAHR"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Robot. Autom. Lett."],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1109\/lra.2024.3522756","type":"journal-article","created":{"date-parts":[[2024,12,25]],"date-time":"2024-12-25T14:38:20Z","timestamp":1735137500000},"page":"1593-1600","source":"Crossref","is-referenced-by-count":0,"title":["Positive-Unlabeled Constraint Learning for Inferring Nonlinear Continuous Constraints Functions From Expert Demonstrations"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9346-1858","authenticated-orcid":false,"given":"Baiyu","family":"Peng","sequence":"first","affiliation":[{"name":"LASA, School of Engineering, EPFL (Swiss Federal Institute of Technology in Lausanne), Lausanne, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7076-8010","authenticated-orcid":false,"given":"Aude","family":"Billard","sequence":"additional","affiliation":[{"name":"LASA, School of Engineering, EPFL (Swiss Federal Institute of Technology in Lausanne), Lausanne, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"issue":"1","key":"ref1","first-page":"1437","article-title":"A comprehensive survey on safe reinforcement learning","volume":"16","author":"Garcia","year":"2015","journal-title":"J. Mach. Learn. Res."},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1147\/JRD.2019.2940428"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-44051-0_14"},{"key":"ref4","article-title":"Maximum likelihood constraint inference for inverse reinforcement learning","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Scobee","year":"2020"},{"key":"ref5","article-title":"Learning behavioral soft constraints from demonstrations","volume-title":"Proc. Workshop Safe Robust Contr. Uncertain Syst. NeurIPS 2021","author":"Glazier","year":"2021"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CCTA48906.2021.9658862"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA46639.2022.9811705"},{"key":"ref8","first-page":"7390","article-title":"Inverse constrained reinforcement learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Malik","year":"2021"},{"key":"ref9","article-title":"Benchmarking constraint inference in inverse reinforcement learning","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Liu","year":"2023"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2023.3333246"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.2974427"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3148436"},{"key":"ref13","first-page":"1211","article-title":"Learning parametric constraints in high dimensions from demonstrations","volume-title":"Proc. Conf. Robot Learn.","author":"Chou","year":"2020"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-020-05877-5"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/tnn.1998.712192"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.4304\/jcp.4.1.94-101"},{"issue":"5","key":"ref17","first-page":"1463","article-title":"Clustering-based method for positive and unlabeled text categorization enhanced by improved TFIDF","volume":"30","author":"Liu","year":"2014","journal-title":"J. Inf. Sci. Eng."},{"key":"ref18","first-page":"9133","article-title":"Responsive safety in reinforcement learning by PID Lagrangian methods","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Stooke","year":"2020"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2019.2893676"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3175595"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/IV48863.2021.9575205"},{"article-title":"Proximal policy optimization algorithms","year":"2017","author":"Schulman","key":"ref22"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s10514-017-9636-y"}],"container-title":["IEEE Robotics and Automation Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/7083369\/10805214\/10816130.pdf?arnumber=10816130","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T18:47:34Z","timestamp":1763578054000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10816130\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2]]},"references-count":23,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/lra.2024.3522756","relation":{},"ISSN":["2377-3766","2377-3774"],"issn-type":[{"type":"electronic","value":"2377-3766"},{"type":"electronic","value":"2377-3774"}],"subject":[],"published":{"date-parts":[[2025,2]]}}}