.. Dueling Bandit Toolkit documentation master file

Welcome to Dueling Bandit Toolkit's Documentation!
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The **Dueling Bandit Toolkit** is a Python package for preference-based online learning using dueling bandit algorithms. It implements algorithms like PARWiS, Contextual PARWiS, RL PARWiS, Double Thompson Sampling, and a Random Pair baseline, with support for synthetic and real-world datasets (Jester, MovieLens).

This documentation is based on the research paper *PARWiS: Winner determination under shoestring budgets using active pairwise comparisons* by Shailendra Bhandari, providing an overview, methodology, experimental results, and API references.

.. toctree::
   :maxdepth: 2
   :caption: Contents:

   introduction
   methodology
   experiments
   api
   references

Indices and tables
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* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`