Multi-Agent Reinforcement Learning on SMAC 8m (Disparity and Hit Point Metrics) benchmark leaderboard · SOTA2 Research

Multi-Agent Reinforcement Learning on SMAC 8m (Disparity and Hit Point Metrics)

87Disparity (Dis-1)IBAL

Evaluation Results

Method	Links
IBAL2026.05		87	92.3	89.8	20	72.3
WALL2026.05		25.4	66.7	70.8	1.7	41.1
Rand-Act2026.05		22.3	34	41.2	0	24.4
FGSM2026.05		21.9	58	64.6	1	36.4
ROMANCE2026.05		18.8	62	58.3	0.7	35.9
Vanilla QMIX2026.05		13.3	54.3	52.5	0	30
Rand-Obs2026.05		10.4	42.3	43.8	0	24.1
ERNIE2026.05		8.3	32.7	53.1	0	23.5
ATLA2026.05		5.2	45.7	50	0	25.2