Name
Title | ||
|---|---|---|
Fast Adaptation to External Agents via Meta Imitation Counterfactual Regret Advantage. |
Abstract | ||
|---|---|---|
This paper focuses on the multi-agent credit assignment problem. We propose a novel multi-agent reinforcement learning algorithm called meta imitation counterfactual regret advantage (MICRA) and a three-phase framework for training, adaptation, and execution of MICRA. The key features are: (1) a counterfactual regret advantage is proposed to optimize the target agents' policy; (2) a meta-imitator is designed to infer the external agents' policies. Results show that MICRA outperforms state-of-the-art algorithms. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.5555/3463952.3464209 | AAMAS |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| mingyue zhang | 1 | 13 | 10.00 |
| Zhi Jin | 2 | 1493 | 137.87 |
| Yang Xu | 3 | 16 | 5.33 |
| Zehan Shen | 4 | 0 | 0.34 |
| Kun Liu | 5 | 0 | 1.01 |
| Keyu Pan | 6 | 0 | 0.34 |