The Balloon Learning Environment - flying stratospheric balloons with deep reinforcement learning.

Overview

Balloon Learning Environment

Docs



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

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

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)
Owner
Google
Google ❤️ Open Source
Google
CLIP2Video: Mastering Video-Text Retrieval via Image CLIP

CLIP2Video: Mastering Video-Text Retrieval via Image CLIP The implementation of paper CLIP2Video: Mastering Video-Text Retrieval via Image CLIP. CLIP2

168 Dec 29, 2022
Memory Efficient Attention (O(sqrt(n)) for Jax and PyTorch

Memory Efficient Attention This is unofficial implementation of Self-attention Does Not Need O(n^2) Memory for Jax and PyTorch. Implementation is almo

Amin Rezaei 126 Dec 27, 2022
VIMPAC: Video Pre-Training via Masked Token Prediction and Contrastive Learning

This is a release of our VIMPAC paper to illustrate the implementations. The pretrained checkpoints and scripts will be soon open-sourced in HuggingFace transformers.

Hao Tan 74 Dec 03, 2022
MG-GCN: Scalable Multi-GPU GCN Training Framework

MG-GCN MG-GCN: multi-GPU GCN training framework. For more information, please read our paper. After cloning our repository, run git submodule update -

Translational Data Analytics (TDA) Lab @GaTech 6 Oct 24, 2022
Privacy-Preserving Portrait Matting [ACM MM-21]

Privacy-Preserving Portrait Matting [ACM MM-21] This is the official repository of the paper Privacy-Preserving Portrait Matting. Jizhizi Li∗, Sihan M

Jizhizi_Li 212 Dec 27, 2022
UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss

UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss This repository contains the TensorFlow implementation of the paper UnF

Simon Meister 270 Nov 06, 2022
A Data Annotation Tool for Semantic Segmentation, Object Detection and Lane Line Detection.(In Development Stage)

Data-Annotation-Tool How to Run this Tool? To run this software, follow the steps: git clone https://github.com/Autonomous-Car-Project/Data-Annotation

TiVRA AI 13 Aug 18, 2022
Must-read Papers on Physics-Informed Neural Networks.

PINNpapers Contributed by IDRL lab. Introduction Physics-Informed Neural Network (PINN) has achieved great success in scientific computing since 2017.

IDRL 330 Jan 07, 2023
GND-Nets (Graph Neural Diffusion Networks) in TensorFlow.

GNDC For submission to IEEE TKDE. Overview Here we provide the implementation of GND-Nets (Graph Neural Diffusion Networks) in TensorFlow. The reposit

Wei Ye 3 Aug 08, 2022
Multi-Stage Episodic Control for Strategic Exploration in Text Games

XTX: eXploit - Then - eXplore Requirements First clone this repo using git clone https://github.com/princeton-nlp/XTX.git Please create two conda envi

Princeton Natural Language Processing 9 May 24, 2022
wlad 2 Dec 19, 2022
General-purpose program synthesiser

DeepSynth General-purpose program synthesiser. This is the repository for the code of the paper "Scaling Neural Program Synthesis with Distribution-ba

Nathanaël Fijalkow 24 Oct 23, 2022
Code for our EMNLP 2021 paper “Heterogeneous Graph Neural Networks for Keyphrase Generation”

GATER This repository contains the code for our EMNLP 2021 paper “Heterogeneous Graph Neural Networks for Keyphrase Generation”. Our implementation is

Jiacheng Ye 12 Nov 24, 2022
Recognize Handwritten Digits using Deep Learning on the browser itself.

MNIST on the Web An attempt to predict MNIST handwritten digits from my PyTorch model from the browser (client-side) and not from the server, with the

Harjyot Bagga 7 May 28, 2022
Event-forecasting - Event Forecasting Algorithms With Python

event-forecasting Event Forecasting Algorithms Theory Correlating events in comp

Intellia ICT 4 Feb 15, 2022
A Python framework for conversational search

Chatty Goose Multi-stage Conversational Passage Retrieval: An Approach to Fusing Term Importance Estimation and Neural Query Rewriting Installation Ma

Castorini 36 Oct 23, 2022
Code for the paper Language as a Cognitive Tool to Imagine Goals in Curiosity Driven Exploration

IMAGINE: Language as a Cognitive Tool to Imagine Goals in Curiosity Driven Exploration This repo contains the code base of the paper Language as a Cog

Flowers Team 26 Dec 22, 2022
Session-aware Item-combination Recommendation with Transformer Network

Session-aware Item-combination Recommendation with Transformer Network 2nd place (0.39224) code and report for IEEE BigData Cup 2021 Track1 Report EDA

Tzu-Heng Lin 6 Mar 10, 2022
PantheonRL is a package for training and testing multi-agent reinforcement learning environments.

PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.

Stanford Intelligent and Interactive Autonomous Systems Group 57 Dec 28, 2022
a spacial-temporal pattern detection system for home automation

Argos a spacial-temporal pattern detection system for home automation. Based on OpenCV and Tensorflow, can run on raspberry pi and notify HomeAssistan

Angad Singh 133 Jan 05, 2023