PPO on RBC2D-medium-v0 (FluidGym)

This repository is part of the FluidGym benchmark results. It contains trained Stable Baselines3 agents for the specialized RBC2D-medium-v0 environment.

Evaluation Results

Global Performance (Aggregated across 5 seeds)

Mean Reward: 0.06 ± 0.15

Per-Seed Statistics

Run Mean Reward Std Dev
Seed 0 -0.06 1.56
Seed 1 0.27 1.35
Seed 2 0.21 0.93
Seed 3 -0.12 1.43
Seed 4 0.00 1.38

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")

References

Downloads last month
-
Video Preview
loading

Collection including safe-autonomous-systems/ma-ppo-RBC2D-medium-v0

Paper for safe-autonomous-systems/ma-ppo-RBC2D-medium-v0

Evaluation results