Learning to Communicate with Deep Multi-Agent Reinforcement Learning
GPTKB entity
Statements (19)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:academic_journal
|
| gptkbp:arXivID |
1605.06676
|
| gptkbp:author |
gptkb:Shimon_Whiteson
gptkb:Nando_de_Freitas Jakob Foerster Yannis M. Assael |
| gptkbp:citation |
over 1000
|
| gptkbp:contribution |
introduces differentiable inter-agent communication in deep reinforcement learning
proposes CommNet architecture |
| gptkbp:field |
gptkb:artificial_intelligence
gptkb:machine_learning multi-agent reinforcement learning |
| https://www.w3.org/2000/01/rdf-schema#label |
Learning to Communicate with Deep Multi-Agent Reinforcement Learning
|
| gptkbp:language |
English
|
| gptkbp:publicationYear |
2016
|
| gptkbp:publishedIn |
gptkb:Advances_in_Neural_Information_Processing_Systems
|
| gptkbp:url |
https://arxiv.org/abs/1605.06676
|
| gptkbp:bfsParent |
gptkb:NeurIPS_2016
|
| gptkbp:bfsLayer |
6
|