| dc.date.accessioned | 2020-10-14T19:06:10Z | |
| dc.date.available | 2020-10-14T19:06:10Z | |
| dc.date.issued | 2020-08-28 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/127995 | |
| dc.description.abstract | The Mission-ready reinforcement learning (MeRLin) program is looking to solve complex planning and coordination problems across a range of Department of Defense mission areas. MeRLin is focusing on developing and training Deep reinforcement learning (DRL) algorithms capable of maintaining performance on complex tasks with human allies. | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | MIT Lincoln Laboratory | en_US |
| dc.relation.ispartofseries | The Bulletin; | |
| dc.rights | Attribution-NoDerivs 3.0 United States | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nd/3.0/us/ | * |
| dc.subject | Supercomputing | en_US |
| dc.subject | Artificial Intelligence | en_US |
| dc.subject | Lincoln Laboratory | en_US |
| dc.subject | LLSC | en_US |
| dc.title | Mission-ready Reinforcement Learning | en_US |
| dc.type | Article | en_US |
