Multi-agent Reinforcement Learning on TrafficJunction Large (TJ-L)
-24.6RewardST
Evaluation results
| Method | Links | |
|---|---|---|
| STAttack rate=0.252026.05 | -24.6 | |
| MLAttack rate=0.752026.05 | -24.7 | |
| J-MAttack rate=0.252026.05 | -24.8 | |
| VLAttack rate=0.252026.05 | -24.8 | |
| J-MAttack rate=0.52026.05 | -24.9 | |
| NSAttack rate=0.52026.05 | -24.9 | |
| J-WAttack rate=0.252026.05 | -25 | |
| CBTSAttack rate=0.252026.05 | -25.1 | |
| J-WAttack rate=0.52026.05 | -25.3 | |
| CBTSAttack rate=0.752026.05 | -25.6 | |
| VLAttack rate=0.52026.05 | -26 | |
| STAttack rate=0.52026.05 | -26 | |
| J-MAttack rate=0.752026.05 | -26.1 | |
| NSAttack rate=0.252026.05 | -26.3 | |
| CBTSAttack rate=0.52026.05 | -26.4 | |
| VLAttack rate=0.752026.05 | -26.5 | |
| STAttack rate=0.752026.05 | -26.7 | |
| MMRAttack rate=0.252026.05 | -27 | |
| J-WAttack rate=0.752026.05 | -27.1 | |
| NSAttack rate=0.752026.05 | -27.6 | |
| MMRAttack rate=0.52026.05 | -28.3 | |
| MLAttack rate=0.252026.05 | -28.6 | |
| MLAttack rate=0.52026.05 | -30.1 | |
| MMRAttack rate=0.752026.05 | -32.8 |