rlfit: Fitting Reinforcement Learning Model to Behavior Data under Bandits

Python package companion to the paper "Fitting Reinforcement Learning Modelto Behavior Data under Bandits". This library is collated from the early version code in this repository which was used for the numerical experiments in the paper.

Installation

Using pip

You can install the package via PyPI:

pip install rlfit

Development setup

We manage dependencies through uv. Once you have installed uv you can perform the following commands to set up a development environment:

1. Clone the repository:

   git clone https://github.com/nrgrp/rlfit.git
   cd rlfit
   

2. Create a virtual environment and install dependencies:

   make install
   

This will:

• Create a Python 3.12 virtual environment.
• Install all dependencies from pyproject.toml.

Usage

The core module is the RLFit class, which was implemented following the scikit-learn style. See the example notebooks and the corresponding paper for some basic usages. If a development environment is configured, executing

make jupyter

will install and start the jupyter lab.