This is PyTorch implementation of Discovering Incremental Skills (DISk) [OpenReview] [Presentation] [Website] [Arxiv].
If you use this code in your research project please cite us as:
@inproceedings{shafiullah2021one,
title={One After Another: Learning Incremental Skills for a Changing World},
author={Shafiullah, Nur Muhammad Mahi and Pinto, Lerrel},
booktitle={International Conference on Learning Representations},
year={2021}
}
We assume you have access to a gpu that can run CUDA 11.3. Then, the simplest way to install all required dependencies is to create an anaconda environment and activate it:
conda env create -f conda_env.yml
conda activate disk
Unfortunately, our experiments require you to install MuJoCo version 1.50 because of a bug in OpenAI Gym MuJoCo environments. You can download the older MuJoCo version and use a free license key, all from here.
To train an SAC agent on the Ant-v3 task run:
python train.py env=ant
This will produce exp folder, where all the outputs are going to be stored including train/eval logs, and evaluation episode videos. Some data will also be stores in Weights and Biases for further analysis.
A video is worth a thousand figures, so here you go.
