SMAC
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Exposure Intensity evaluation | SMAC II 1c3s5z (test) | Exposure Intensity2.1 | 24 | |
| Exposure Intensity evaluation | SMAC MMM v2 (test) | Exposure Intensity3.03 | 24 | |
| Exposure Intensity evaluation | SMAC II 8m v2 (test) | Exposure Intensity2.2 | 24 | |
| Exposure Intensity evaluation | SMAC II 1c3s6z vs 1c3s5z v2 (test) | Exposure Intensity2.45 | 24 | |
| Adversary Reward | SMAC 1c3s5z II | Adversary Reward18.87 | 24 | |
| Adversary Reward | SMAC MMM II | Adversary Reward19.16 | 24 | |
| Adversary Reward | SMAC 8m II | Adversary Reward17.07 | 24 | |
| Adversary Reward | SMAC 1c3s6z vs 1c3s5z II | Adversary Reward19.41 | 24 | |
| Multi-Agent Reinforcement Learning | SMAC v2 (test) | Win Rate (Protoss 5 Units)84 | 24 | |
| Multi-Agent Reinforcement Learning | SMAC Avg. v1 | Normalized Win Rate1.006 | 18 | |
| Multi-Agent Reinforcement Learning | SMAC 6h* v1 | Normalized Win Rate104.9 | 18 | |
| Multi-Agent Reinforcement Learning | SMAC 3s5z v1 | Normalized Win Rate99.4 | 18 | |
| Multi-Agent Reinforcement Learning | SMAC 2s3z v1 | Normalized Win Rate100.2 | 18 | |
| Multi-Agent Reinforcement Learning | SMAC 3m v1 | Normalized Win Rate100.9 | 18 | |
| Multi-Agent Reinforcement Learning | SMAC maps | 5m_vs_6m Score59 | 18 | |
| Multi-agent Coordination | SMAC 1o10b_vs_1r | Win Rate65 | 16 | |
| Multi-Agent Reinforcement Learning | SMAC corridor v2 | Win Rate79.2 | 15 | |
| Multi-Agent Reinforcement Learning | SMAC 5m_vs_6m v2 | Win Rate53.9 | 15 | |
| Multi-Agent Reinforcement Learning | SMAC 3s5z vs 3s6z v2 | Win Rate0.801 | 15 | |
| 5m vs 6m | SMAC | Win Rate93.7 | 13 | |
| Multi-agent reinforcement learning on Unseen Tasks | SMAC Stalker-Zealot Medium quality | 1s3z Performance70.6 | 12 | |
| Multi-Agent Reinforcement Learning | SMAC 2m1z | State Entropy0.038 | 12 | |
| 3s5z vs 3s6z | SMAC | Win Rate96.5 | 12 | |
| 6h vs 8z | SMAC | Win Rate99.8 | 12 | |
| 10m vs 11m | SMAC | Win Rate100 | 12 |
Showing 25 of 202 rows
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