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Cooperative Multi-Agent Reinforcement Learning on SMAC 3m map
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19.8
Return
MAPPO
8.568
11.484
14.4
17.316
Apr 8, 2026
Return
Win Rate
Throughput (TPS)
Updated 9d ago
Evaluation Results
Method
Method
Links
Return
Win Rate
Throughput (TPS)
MAPPO
Configuration=FO
2026.04
19.8
98.12
6.5
QMIX
Configuration=FO
2026.04
19.6
98.77
6.6
KD-MARL
Configuration=LH
2026.04
18.6
94.78
5.5
MAPPO
Configuration=LH
2026.04
18.2
92.65
6.2
VDN
Configuration=FO
2026.04
18
85.42
6
KD-MARL
Configuration=LH+A
2026.04
18
90.39
4.1
QMIX
Configuration=LH
2026.04
16
86.34
5.9
MAPPO
Configuration=LH+A
2026.04
15
80.34
6.3
VDN
Configuration=LH
2026.04
13.5
68.31
5.4
QMIX
Configuration=LH+A
2026.04
12.5
70.27
3.8
VDN
Configuration=LH+A
2026.04
9
52.12
4.3
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