{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T19:13:59Z","timestamp":1778094839961,"version":"3.51.4"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1718420"],"award-info":[{"award-number":["1718420"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100005740","name":"NASA Iowa Space Grant","doi-asserted-by":"publisher","award":["NNX16AL88H"],"award-info":[{"award-number":["NNX16AL88H"]}],"id":[{"id":"10.13039\/100005740","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007065","name":"NVIDIA GPU Grant Program","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007065","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Automat. Sci. Eng."],"published-print":{"date-parts":[[2022,10]]},"DOI":"10.1109\/tase.2022.3151607","type":"journal-article","created":{"date-parts":[[2022,2,21]],"date-time":"2022-02-21T22:08:25Z","timestamp":1645481305000},"page":"2837-2848","source":"Crossref","is-referenced-by-count":51,"title":["Scalable Autonomous Separation Assurance With Heterogeneous Multi-Agent Reinforcement Learning"],"prefix":"10.1109","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0707-1034","authenticated-orcid":false,"given":"Marc","family":"Brittain","sequence":"first","affiliation":[{"name":"Department of Aerospace Engineering, Iowa State University, Ames, IA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8492-5411","authenticated-orcid":false,"given":"Peng","family":"Wei","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Aerospace Engineering, George Washington University, Washington, DC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.17226\/18815"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.2514\/6.2017-3086"},{"key":"ref3","volume-title":"U-Space Blueprint","year":"2017"},{"key":"ref4","volume-title":"Unmanned Aircraft System Traffic Management (UTM) Concept of Operations","author":"Kopardekar","year":"2016"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICNSURV.2019.8735165"},{"key":"ref6","volume-title":"Design Principles and Algorithms for Air Traffic Arrival Scheduling","author":"Erzberger","year":"2014"},{"key":"ref7","article-title":"Air traffic management technology demonstration-1 concept of operations (ATD-1 ConOps), version 3.0","author":"Baxley","year":"2016"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.2514\/2.4678"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.2514\/1.11168"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.2514\/3.20934"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2012.6385823"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.2514\/1.G000218"},{"key":"ref13","first-page":"71","article-title":"Aircraft conflict resolution by genetic algorithm and b-spline approximation","volume-title":"Proc. EIWAC 2nd ENRI Int. Workshop (ATM\/CNS)","author":"Delahaye"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.2514\/1.48475"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.2514\/1.53172"},{"issue":"1","key":"ref16","first-page":"55","article-title":"Next-generation airborne collision avoidance system","volume":"19","author":"Kochenderfer","year":"2012","journal-title":"Lincoln Lab. J."},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.2514\/1.54805"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.2514\/1.54674"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.2514\/1.G001822"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICInfA.2015.7279378"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.2514\/1.G005000"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.2514\/6.2020-1371"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3048360"},{"key":"ref24","article-title":"Robust airborne collision avoidance through dynamic programming","author":"Kochenderfer","year":"2011"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.2514\/1.G003724"},{"key":"ref26","article-title":"StarCraft II: A new challenge for reinforcement learning","author":"Vinyals","year":"2017","journal-title":"arXiv:1708.04782"},{"key":"ref27","first-page":"75","article-title":"High-level reinforcement learning in strategy games","volume-title":"Proc. 9th Int. Conf. Auton. Agents Multiagent Syst. (AAMAS)","volume":"1","author":"Amato"},{"key":"ref28","article-title":"Playing Atari with deep reinforcement learning","author":"Mnih","year":"2013","journal-title":"arXiv:1312.5602"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1038\/nature16961"},{"key":"ref30","first-page":"1","article-title":"Autonomous aircraft sequencing and separation with hierarchical deep reinforcement learning","volume-title":"Proc. Int. Conf. Res. Air Transp.","author":"Brittain"},{"key":"ref31","first-page":"1","article-title":"A machine learning approach for conflict resolution in dense traffic scenarios with uncertainties","volume-title":"Proc. 13th USA\/Europe ATM R&D Seminar","author":"Pham"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.2514\/1.I010807"},{"key":"ref33","first-page":"1","article-title":"Improvement of conflict detection and resolution at high densities through reinforcement learning","volume-title":"Proc. Int. Conf. Res. Air Transp.","author":"Ribeiro"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.3013920"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3025287"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2014.7004541"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CAC51589.2020.9327673"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2018.8593871"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989037"},{"key":"ref40","first-page":"1","article-title":"R-MADDPG for partially observable environments and limited communication","volume-title":"ICML Workshop, Reinforcement Learn. Real Life","author":"Wang"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2016.2603781"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2020.2971324"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.2514\/2.4384"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.2514\/6.2004-4992"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2019.8917217"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.2514\/6.2021-1952"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ITAIC.2019.8785582"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3077572"},{"key":"ref49","article-title":"An autonomous free airspace en-route controller using deep reinforcement learning techniques","author":"Mollinga","year":"2020","journal-title":"arXiv:2007.01599"},{"key":"ref50","article-title":"A deep multi-agent reinforcement learning approach to autonomous separation assurance","author":"Brittain","year":"2020","journal-title":"arXiv:2003.08353"},{"key":"ref51","article-title":"Proximal policy optimization algorithms","author":"Schulman","year":"2017","journal-title":"arXiv:1707.06347"},{"key":"ref52","article-title":"High-dimensional continuous control using generalized advantage estimation","author":"Schulman","year":"2015","journal-title":"arXiv:1506.02438"},{"key":"ref53","first-page":"6379","article-title":"Multi-agent actor-critic for mixed cooperative-competitive environments","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Lowe"},{"key":"ref54","first-page":"1","article-title":"Bluesky atc simulator project: An open data and open source approach","volume-title":"Proc. 7th Int. Conf. Res. Air Transp.","author":"Hoekstra"},{"key":"ref55","first-page":"561","article-title":"Ray: A distributed framework for emerging ai applications","volume-title":"Proc. 13th USENIX Symp. Operating Syst. Design Implement. (OSDI)","author":"Moritz"},{"key":"ref56","article-title":"Dealing with non-stationarity in multi-agent deep reinforcement learning","author":"Papoudakis","year":"2019","journal-title":"arXiv:1906.04737"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-71050-9"}],"container-title":["IEEE Transactions on Automation Science and Engineering"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/8856\/9918179\/9717997-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8856\/9918179\/09717997.pdf?arnumber=9717997","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,17]],"date-time":"2024-01-17T22:58:11Z","timestamp":1705532291000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9717997\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10]]},"references-count":57,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tase.2022.3151607","relation":{},"ISSN":["1545-5955","1558-3783"],"issn-type":[{"value":"1545-5955","type":"print"},{"value":"1558-3783","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10]]}}}