safe-autonomous-systems / sac-Airfoil2D-easy-v0

huggingface.co
Total runs: 20
24-hour runs: -3
7-day runs: 2
30-day runs: -1
Model's Last Updated: February 04 2026
reinforcement-learning

Introduction of sac-Airfoil2D-easy-v0

Model Details of sac-Airfoil2D-easy-v0

SAC on Airfoil2D-easy-v0 (FluidGym)

This repository is part of the FluidGym benchmark results. It contains trained Stable Baselines3 agents for the specialized Airfoil2D-easy-v0 environment.

Evaluation Results
Global Performance (Aggregated across 5 seeds)

Mean Reward: 1.70 ± 0.01

Per-Seed Statistics
Run Mean Reward Std Dev
Seed 0 1.71 0.24
Seed 1 1.71 0.23
Seed 2 1.69 0.23
Seed 3 1.70 0.25
Seed 4 1.71 0.23
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 sac-Airfoil2D-easy-v0 on huggingface.co

20
Total runs
-3
24-hour runs
0
3-day runs
2
7-day runs
-1
30-day runs

More Information About sac-Airfoil2D-easy-v0 huggingface.co Model

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sac-Airfoil2D-easy-v0 install

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Url of sac-Airfoil2D-easy-v0

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