| dc.contributor.author | Luis, Juan Jose Garau | |
| dc.contributor.author | Crawley, Edward | |
| dc.contributor.author | Cameron, Bruce | |
| dc.date.accessioned | 2022-09-08T17:06:49Z | |
| dc.date.available | 2022-09-08T17:06:49Z | |
| dc.date.issued | 2021 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/145325 | |
| dc.language.iso | en | |
| dc.publisher | IEEE | en_US |
| dc.relation.isversionof | 10.1109/AERO50100.2021.9438291 | en_US |
| dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | en_US |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en_US |
| dc.source | MIT web domain | en_US |
| dc.title | Applicability and Challenges of Deep Reinforcement Learning for Satellite Frequency Plan Design | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Luis, Juan Jose Garau, Crawley, Edward and Cameron, Bruce. 2021. "Applicability and Challenges of Deep Reinforcement Learning for Satellite Frequency Plan Design." 2021 IEEE Aerospace Conference (50100). | |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics | |
| dc.relation.journal | 2021 IEEE Aerospace Conference (50100) | en_US |
| dc.eprint.version | Author's final manuscript | en_US |
| dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
| eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
| dc.date.updated | 2022-09-08T17:03:53Z | |
| dspace.orderedauthors | Luis, JJG; Crawley, E; Cameron, B | en_US |
| dspace.date.submission | 2022-09-08T17:03:57Z | |
| mit.license | OPEN_ACCESS_POLICY | |
| mit.metadata.status | Authority Work and Publication Information Needed | en_US |
