Balloon Learning Environment
The Balloon Learning Environment (BLE) is a simulator for stratospheric balloons. It is designed as a benchmark environment for deep reinforcement learning algorithms, and is a followup to the Nature paper "Autonomous navigation of stratospheric balloons using reinforcement learning".
Getting Started
Note: The BLE requires python >= 3.7
The BLE can easily be installed with pip:
$ pip install --upgrade pip
$ pip install balloon_learning_environment
To install with the acme package:
$ pip install --upgrade pip
$ pip install balloon_learning_environment[acme]
Once the package has been installed, you can test it runs correctly by evaluating one of the benchmark agents:
python -m balloon_learning_environment.eval.eval \
--agent=station_seeker \
--renderer=matplotlib \
--suite=micro_eval \
--output_dir=/tmp/ble/eval
To install from GitHub directly, run the following commands from the root directory where you cloned the repository:
$ pip install --upgrade pip
$ pip install .[acme]
Ensure the BLE is Using Your GPU/TPU
The BLE contains a VAE for generating winds, which you will probably want to run on your accelerator. See the jax documentation for installing with GPU or TPU.
As a sanity check, you can open interactive python and run:
from balloon_learning_environment.env import balloon_env
env = balloon_env.BalloonEnv()
If you are not running with GPU/TPU, you should see a log like:
WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)
If you don't see this log, you should be good to go!
Next Steps
For more information, see the docs.
Giving credit
If you use the Balloon Learning Environment in your work, we ask that you use the following BibTeX entry:
@software{Greaves_Balloon_Learning_Environment_2021,
author = {Greaves, Joshua and Candido, Salvatore and Dumoulin, Vincent and Goroshin, Ross and Ponda, Sameera S. and Bellemare, Marc G. and Castro, Pablo Samuel},
month = {12},
title = {{Balloon Learning Environment}},
url = {https://github.com/google/balloon-learning-environment},
version = {1.0.0},
year = {2021}
}
If you use the ble_wind_field dataset, you should also cite
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz‐Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A.,
Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G.,
Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M.,
Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L.,
Healy, S., Hogan, R.J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P.,
Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F.,
Villaume, S., Thépaut, J-N. (2017): Complete ERA5: Fifth generation of ECMWF
atmospheric reanalyses of the global climate. Copernicus Climate Change Service
(C3S) Data Store (CDS). (Accessed on 01-04-2021)
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