cuic0808 / rlssm

Bayesian Parameter Estimation (based on pystan) of reinforcement learning and sequential sampling models, and combinations of the two.

rlssm

rlssm is a Python package for fitting reinforcement learning (RL) models, sequential sampling models (DDM, RDM, LBA, ALBA, and ARDM), and combinations of the two, using Bayesian parameter estimation.

Parameter estimation is done at an individual or hierarchical level using PyStan, the Python Interface to Stan. Stan performs Bayesian inference using the No-U-Turn sampler, a variant of Hamiltonian Monte Carlo.

Install

You can install the rlssm package using:

pip install rlssm

Make sure you have the dependecies installed first.

Dependencies

• pystan=2.19
• pandas
• scipy
• seaborn

Conda environment (suggested)

If you have Andaconda or miniconda installed and you would like to create a separate environment:

conda create --n stanenv python=3 pandas scipy seaborn pystan=2.19
conda activate stanenv
pip install rlssm

Documentation

The latest documentation can be found here: https://rlssm.readthedocs.io/

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