OpenSpiel Reproductions

Results reproductions for several core algorithms implemented in the OpenSpiel framework for learning in games. Individual experiments may be run using scripts in the algorithms foler. SLURM jobfiles can also be constructed and batch run with run.py.

If you use OpenSpiel in your research please cite the originating paper:

@article{LanctotEtAl2019OpenSpiel,
  title     = {{OpenSpiel}: A Framework for Reinforcement Learning in Games},
  author    = {Marc Lanctot and Edward Lockhart and Jean-Baptiste Lespiau and
               Vinicius Zambaldi and Satyaki Upadhyay and Julien P\'{e}rolat and
               Sriram Srinivasan and Finbarr Timbers and Karl Tuyls and
               Shayegan Omidshafiei and Daniel Hennes and Dustin Morrill and
               Paul Muller and Timo Ewalds and Ryan Faulkner and J\'{a}nos Kram\'{a}r
               and Bart De Vylder and Brennan Saeta and James Bradbury and David Ding
               and Sebastian Borgeaud and Matthew Lai and Julian Schrittwieser and
               Thomas Anthony and Edward Hughes and Ivo Danihelka and Jonah Ryan-Davis},
  year      = {2019},
  eprint    = {1908.09453},
  archivePrefix = {arXiv},
  primaryClass = {cs.LG},
  journal   = {CoRR},
  volume    = {abs/1908.09453},
  url       = {http://arxiv.org/abs/1908.09453},
}

The report associated with this reproduction is availible here:

@misc{walton2021multiagent,
      title={Multi-agent Reinforcement Learning in OpenSpiel: A Reproduction Report}, 
      author={Michael Walton and Viliam Lisy},
      year={2021},
      eprint={2103.00187},
      archivePrefix={arXiv},
      primaryClass={cs.AI}
}