ActionNoise Wrapper

To learn and evaluate control policies to noisy actuators, FluidGym provides the ActionNoise wrapper, which adds noise to the actions taken by the agent. This is particularly useful for simulating real-world scenarios where actuators may not perform perfectly.

FluidGym wrappers can be used by importing them from the fluidgym.wrappers module and wrapping the environment instance.

Here is a simple example from examples/wrappers/action_noise.py:

import fluidgym
from fluidgym.wrappers import ActionNoise

env = fluidgym.make(
    "CylinderJet2D-easy-v0",
)

# Now, we add action noise to the environment's actions
env = ActionNoise(env, sigma=0.1, seed=42)

obs, info = env.reset(seed=42)

action = env.sample_action()

# Now, if we take a step, the action will have noise added to it
obs, reward, terminated, truncated, info = env.step(action)