This is the official implementation of the method proposed in
@article{salehi2022few,
title={Few-shot Quality-Diversity Optimization},
author={Salehi, Achkan and Coninx, Alexandre and Doncieux, Stephane},
journal={IEEE Robotics and Automation Letters},
year={2022},
publisher={IEEE}
}.
https://arxiv.org/pdf/2109.06826.pdf
-
Python 3.6+
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Metaworld v2 benchmark (https://github.com/rlworkgroup/metaworld)
-
In case you want to reproduce the experiments based on random maze distributions:
- LibFastSim (https://github.com/jbmouret/libfastsim)
- PyFastSim (https://github.com/alexendy/pyfastsim)
- fastSimGym (https://github.com/alexendy/fastsim\_gym)
Other requirements can be found in requirements.txt
.
The results of the paper can be reproduced via
$ cd NS
$ python -m scoop -n <num_procs> population_priors.py <args>
For the maze experiments, you will need to generate random mazes using the script FAERY-original/environments/maze_generator/maze_generator.py
.