Inverse Contextual Bandits: Learning How Behavior Evolves over Time

Code author: Alihan Hüyük (ah2075@cam.ac.uk)

This repository contains the necessary code to replicate the main experimental results in the ICML 2022 paper 'Inverse Contextual Bandits: Learning How Behavior Evolves over Time.' Our proposed methods, Bayesian ICB and Nonparametric Bayesian ICB, are implemented in src/main-bicb.py and src/main-nbicb.py respectively.

Usage

First, install the required python packages by running:

    python -m pip install -r requirements.txt

Then, the main experimental results in the paper can be replicated by running:

    ./run.sh
    python src/eval1.py  # Table 2
    python src/eval2.py  # Table 3

Note that, in order to run these experiments, you need to get access to the Organ Procurement and Transplantation Network (OPTN) dataset for liver transplantations as of December 4, 2020.

Citing

If you use this software please cite as follows:

@inproceedings{huyuk2022inverse,
  author={Alihan H\"uy\"uk and Daniel Jarrett and Mihaela van der Schaar},
  title={Inverse contextual bandits: Learning how behavior evolves over time},
  booktitle={Proceedings of the 39th International Conference on Machine Learning (ICML)},
  year={2022}
}