Fitting reinforcement learning model to behavior data under bandits.
Project description
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:
-
Clone the repository:
git clone https://github.com/nrgrp/rlfit.git cd rlfit
-
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.
Project details
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