This repository is part of the
FluidGym
benchmark results. It contains trained Stable Baselines3 agents for the specialized
RBC2D-easy-v0
environment.
Evaluation Results
Global Performance (Aggregated across 5 seeds)
Mean Reward:
0.65 ± 0.09
Per-Seed Statistics
Run
Mean Reward
Std Dev
Seed 0
0.63
0.19
Seed 1
0.70
0.24
Seed 2
0.77
0.25
Seed 3
0.66
0.28
Seed 4
0.49
0.15
About FluidGym
FluidGym is a benchmark for reinforcement learning in active flow control.
Usage
Each seed is contained in its own subdirectory. You can load a model using:
from stable_baselines3 import SAC
model = SAC.load("0/ckpt_latest.zip")
Runs of safe-autonomous-systems ma-sac-RBC2D-easy-v0 on huggingface.co
10
Total runs
3
24-hour runs
6
3-day runs
10
7-day runs
8
30-day runs
More Information About ma-sac-RBC2D-easy-v0 huggingface.co Model
ma-sac-RBC2D-easy-v0 huggingface.co
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