Welcome to SMPyBandits documentation!¶
Open-Source Python package for Single- and Multi-Players multi-armed Bandits algorithms.
A research framework for Single and Multi-Players Multi-Arms Bandits (MAB) Algorithms: UCB, KL-UCB, Thompson and many more for single-players, and MCTopM & RandTopM, MusicalChair, ALOHA, MEGA, rhoRand for multi-players simulations. It runs on Python 2 and 3, and is publically released as an open-source software under the MIT License.
Note
See more on the GitHub page for this project: https://github.com/SMPyBandits/SMPyBandits/. The project is also hosted on Inria GForge, and the documentation can be seen online at https://smpybandits.github.io/ or http://http://banditslilian.gforge.inria.fr/ or https://smpybandits.readthedocs.io/.
This repository contains the code of my numerical environment, written in Python, in order to perform numerical simulations on single-player and multi-players Multi-Armed Bandits (MAB) algorithms.
I (Lilian Besson) have started my PhD in October 2016, and this is a part of my on going research since December 2016.
How to cite this work?¶
If you use this package for your own work, please consider citing it with this piece of BibTeX:
@misc{SMPyBandits,
title = {{SMPyBandits: an Open-Source Research Framework for Single and Multi-Players Multi-Arms Bandits (MAB) Algorithms in Python}},
author = {Lilian Besson},
year = {2018},
url = {https://github.com/SMPyBandits/SMPyBandits/},
howpublished = {Online at: \url{GitHub.com/SMPyBandits/SMPyBandits}},
note = {Code at https://github.com/SMPyBandits/SMPyBandits/, documentation at https://smpybandits.github.io/}
}
I also wrote a small paper to present SMPyBandits, and I will send it to JMLR MLOSS. The paper can be consulted here on my website.
- SMPyBandits
- SMPyBandits modules
- How to run the code ?
- List of research publications using Lilian Besson’s SMPyBandits project
- Policy aggregation algorithms
- Multi-players simulation environment
- Doubling Trick for Multi-Armed Bandits
- Structure and Sparsity of Stochastic Multi-Armed Bandits
- Non-Stationary Stochastic Multi-Armed Bandits
- Short documentation of the API
- About parallel computations
- 💥 TODO
- Some illustrations for this project
- Jupyter Notebooks 📓 by Naereen @ GitHub
- List of notebooks for SMPyBandits
- A note on execution times, speed and profiling
- UML diagrams
logs
files
Note
Both this documentation and the code are publicly available, under the open-source MIT License. The code is hosted on GitHub at github.com/SMPyBandits/SMPyBandits.
Indices and tables¶
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