Overview

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

Requirements

• Python 3.6+

• 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.

Usage

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.