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Benchmarks
Multi-Agent Reinforcement Learning on Simple Spread N=10
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1.57
Collisions
CG-CMARL
0.798
6.009
11.22
16.431
Jun 1, 2026
Collisions
Per-pair Interaction
Coverage (%)
Updated 1d ago
Evaluation Results
Method
Method
Links
Collisions
Per-pair Interaction
Coverage (%)
CG-CMARL
lambda=10.00, Pareto-o...
2026.06
1.57
0.03
0.52
CG-CMARL
lambda=5.00, Pareto-op...
2026.06
1.98
0.04
1.85
CG-CMARL
lambda=2.00, Pareto-op...
2026.06
3.43
0.08
12.24
CG-CMARL
lambda=1.00, Pareto-op...
2026.06
5.34
0.12
21.8
CG-CMARL
lambda=0.50, Pareto-op...
2026.06
8.15
0.18
24.69
CG-CMARL
lambda=0.20, Pareto-op...
2026.06
10.74
0.24
27.64
CG-CMARL
lambda=0.10, Pareto-op...
2026.06
11.67
0.26
27.18
CG-CMARL
lambda=0.00, Pareto-op...
2026.06
12.23
0.27
27.14
IQL
local_ratio=0.0
2026.06
20.87
0.46
16.73
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