Multi-agent Reinforcement Learning on SMAC 2c_vs_64zg Homog.
29.8Win RateMetaMind
Evaluation Results
| Method | Links | |
|---|---|---|
| MetaMindMethod Category=Multi-Agent World Model Methods, Execution Protocol=Decentralized, Training Steps=200K, Number of Seeds=1002026.02 | 29.8 | |
| MARIEMethod Category=Multi-Agent World Model Methods, Execution Protocol=CTDE, Training Steps=200K, Number of Seeds=1002026.02 | 23.5 | |
| DCWMCMethod Category=Multi-Agent World Model Methods, Execution Protocol=Decentralized, Training Steps=200K, Number of Seeds=1002026.02 | 9.5 | |
| MAPPOMethod Category=Multi-Agent RL Methods, Execution Protocol=CTDE, Training Steps=200K, Number of Seeds=1002026.02 | 5.2 | |
| MBVDMethod Category=Multi-Agent RL Methods, Execution Protocol=CTDE, Training Steps=200K, Number of Seeds=1002026.02 | 0 |