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Multi-Agent Reinforcement Learning on SMAC MMM

92.7Win Rate (Dis-1)IBAL
49.33260.59171.8583.109May 18, 2026

Evaluation results

MethodLinks
IBAL2026.0592.7——58.194.389.786.784.3
Rand-Act2026.0581.2——10.491.78458.365.1
WALL2026.0577.1——27.19083.782.372.1
Rand-Obs2026.0571.9——8.39388.365.471.2
ROMANCE2026.0571.9——13.59179.361.563.4
ERNIE2026.0569.8——7.389.3774958.5
FGSM2026.0567.3——3.1957752.158.9
ATLA2026.0565.6——8.391.783.75160.1
Vanilla QMIX2026.0551——187.77439.650.2
DG-MAPPODifficulty=Easy, Sight Range=92026.01—1001.6—————
HAPPODifficulty=Easy, Sight Range=92026.01—81.222.9—————
MAPPODifficulty=Easy, Sight Range=92026.01—95.64.5—————
MAT-DecDifficulty=Easy, Sight Range=92026.01—98.12.1—————