This project provides scripts for running several OpenAI Baselines algorithms on all MuJoCo or Roboschool gym environments in order to compare algorithm performance.

The following Python packages are required:

gym

roboschool (Only required if you want to run Roboschool environments)

baselines (Note: baselines must be installed from source. A pip install will give you an outdated version)

matplotlib

argparse

os

The MuJoCo software, mjpro150 is required to run the MuJoCo environments. The MuJoCo submodule for gym is also required, which can be installed via

pip install gym[mujoco]

Run the bash script by typing

./runExperiments.sh

The bash script accepts the following positional command line arguments:

1: Subdirectory to save training data in. Default is data.

2: mujoco or roboschool - Choose which environment set to run. Default is roboschool.

3: Number of timesteps to run each algorithm. Defualt is 1000000.

4: Number of random seeds to run for each algorithm. Default is 3.

For example, to save data to a subdirectory called "test", run the MuJoCo environments for 10000 timesteps with each algorithm, and run 5 different seeds for each algorithm, you would type

./runExperiments.sh test mujoco 10000 5

Plots of all learning curves are saved as pdf files in a subfolder inside the data folder called plots. These plots show the episode reward vs. number of timesteps, and the smoothing function from the baselines plot utility is applied. The shaded regions represent the variations across all seeds, and the solid line represents the mean across all seeds.

Notices:

Copyright 2019 United States Government as represented by the Administrator of the National Aeronautics and Space Administration. No copyright is claimed in the United States under Title 17, U.S. Code. All Other Rights Reserved.

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