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DPE code - Code used in "Optimal Algorithms for Multiplayer Multi-Armed Bandits" (AISTATS 2020)

License: MIT License

Python 73.08% Jupyter Notebook 26.92%

dpe's Introduction

DPE

Code used in "Optimal Algorithms for Multiplayer Multi-Armed Bandits" - Po-An Wang, Alexandre Proutiere, Kaito Ariu, Yassir Jedra, Alessio Russo, Proceedings AISTATS 2020.

Code Author: Alessio Russo

License

Our code is released under the MIT License (refer to the LICENSE file for details).

Requirements

  • Python 3.7
  • numpy 1.16.1
  • matplotlib
  • cython (for pyximport)

Simulations

To do the simulations, first create scores/ and figures/ repositories. Then run the notebook file. If you decide to run a new simulations with different parameters, first delete all the content in the "scores" folder, or copy it somewhere else if you need it.

Cite

If you find this code useful in your research, please, consider citing it:

@misc{dpe2020, author = {Alessio Russo}, title = {DPE Algorithms}, year = 2020, doi = {10.5281/zenodo.3783611}, url = { https://doi.org/10.5281/zenodo.3783611 } }

and/or cite the paper:

@inproceedings{wang2020optimal, title={Optimal algorithms for multiplayer multi-armed bandits}, author={Wang, Po-An and Proutiere, Alexandre and Ariu, Kaito and Jedra, Yassir and Russo, Alessio}, booktitle={International Conference on Artificial Intelligence and Statistics}, pages={4120--4129}, year={2020} }

DOI MIT license

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Contributors

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