Multi-Agent Reinforcement Learning on SMAC 3s5z vs 3s6z v2
0.801Win RateACL-LFT
Evaluation Results
| Method | Links | |
|---|---|---|
| ACL-LFTRL-Method=QPLEX2025.10 | 0.801 | |
| ACL-LFTRL-Method=QMIX2025.10 | 0.794 | |
| ACL-LFTRL-Method=MAPPO2025.10 | 0.789 | |
| AMAGORL-Method=QPLEX2025.10 | 0.775 | |
| AMAGORL-Method=QMIX2025.10 | 0.763 | |
| AMAGORL-Method=MAPPO2025.10 | 0.761 | |
| MambaRL-Method=QMIX2025.10 | 0.751 | |
| ToSTRL-Method=QPLEX2025.10 | 0.751 | |
| MambaRL-Method=QPLEX2025.10 | 0.75 | |
| ToSTRL-Method=QMIX2025.10 | 0.737 | |
| TransformerRL-Method=QPLEX2025.10 | 0.736 | |
| TransformerRL-Method=QMIX2025.10 | 0.728 | |
| MambaRL-Method=MAPPO2025.10 | 0.726 | |
| ToSTRL-Method=MAPPO2025.10 | 0.722 | |
| TransformerRL-Method=MAPPO2025.10 | 0.715 |