This repository is part of the
FluidGym
benchmark results. It contains trained Stable Baselines3 agents for the specialized
RBC3D-easy-v0
environment.
Evaluation Results
Global Performance (Aggregated across 5 seeds)
Mean Reward:
0.42 ± 0.07
Per-Seed Statistics
Run
Mean Reward
Std Dev
Seed 0
0.37
0.08
Seed 1
0.56
0.10
Seed 2
0.37
0.14
Seed 3
0.38
0.04
Seed 4
0.39
0.05
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-RBC3D-easy-v0 on huggingface.co
9
Total runs
1
24-hour runs
1
3-day runs
5
7-day runs
0
30-day runs
More Information About ma-sac-RBC3D-easy-v0 huggingface.co Model
ma-sac-RBC3D-easy-v0 huggingface.co
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