A variational approach to mutual information-based coordination for multi-agent reinforcement learning
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kim, WooJun | ko |
| dc.contributor.author | Jung, Whiyoung | ko |
| dc.contributor.author | Cho, Myung-Sik | ko |
| dc.contributor.author | Sung, Youngchul | ko |
| dc.date.accessioned | 2022-11-25T06:00:53Z | - |
| dc.date.available | 2022-11-25T06:00:53Z | - |
| dc.date.created | 2022-11-25 | - |
| dc.date.created | 2022-11-25 | - |
| dc.date.issued | 2022-07-23 | - |
| dc.identifier.citation | ICML 2022 Workshop AI for Agent-Based Modelling, AI4ABM | - |
| dc.identifier.uri | http://hdl.handle.net/10203/300994 | - |
| dc.language | English | - |
| dc.publisher | ICML | - |
| dc.title | A variational approach to mutual information-based coordination for multi-agent reinforcement learning | - |
| dc.type | Conference | - |
| dc.type.rims | CONF | - |
| dc.citation.publicationname | ICML 2022 Workshop AI for Agent-Based Modelling, AI4ABM | - |
| dc.identifier.conferencecountry | US | - |
| dc.identifier.conferencelocation | Baltimore, Maryland | - |
| dc.contributor.localauthor | Sung, Youngchul | - |
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