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This repository is part of the
FluidGym
benchmark results. It contains trained Stable Baselines3 agents for the specialized
RBC3D-hard-v0
environment.
Evaluation Results
Global Performance (Aggregated across 5 seeds)
Mean Reward:
0.34 ± 0.01
Per-Seed Statistics
Run
Mean Reward
Std Dev
Seed 0
0.35
0.05
Seed 1
0.35
0.05
Seed 2
0.35
0.07
Seed 3
0.35
0.06
Seed 4
0.31
0.03
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 PPO
model = PPO.load("0/ckpt_latest.zip")
Runs of safe-autonomous-systems ma-ppo-RBC3D-hard-v0 on huggingface.co
0
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
-9
30-day runs
More Information About ma-ppo-RBC3D-hard-v0 huggingface.co Model
ma-ppo-RBC3D-hard-v0 huggingface.co
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safe-autonomous-systems ma-ppo-RBC3D-hard-v0 online free url in huggingface.co:
ma-ppo-RBC3D-hard-v0 is an open source model from GitHub that offers a free installation service, and any user can find ma-ppo-RBC3D-hard-v0 on GitHub to install. At the same time, huggingface.co provides the effect of ma-ppo-RBC3D-hard-v0 install, users can directly use ma-ppo-RBC3D-hard-v0 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
ma-ppo-RBC3D-hard-v0 install url in huggingface.co: