Research map / Multi-agent systems and games / Cooperative multi-agent RL
SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Remove random start positions (ablation) | MAPPO on SMACv2 5-unit scenarios · SMACv2 | win rate | Helped |
| Use only surround or reflect starting-position scenarios rather than combining them (ablation) | MAPPO on SMACv2 5-unit scenarios · SMACv2 | win rate | No clear effect |
| Restrict unit composition to a single non-special unit type (ablation) | MAPPO on SMACv2 5-unit scenarios · SMACv2 | win rate | Helped |
| Use fixed unit sight and attack ranges instead of varied SMACv2 ranges (ablation) | MAPPO on SMACv2 5-unit scenarios · SMACv2 | win rate | Helped |
| Replace the recurrent network with a feed-forward network (ablation) | MAPPO on SMACv2 5-unit scenarios · SMACv2 | win rate | Hurt |
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