Artifact for the IJCAI 2024 paper "Solving Long-run Average Reward Robust MDPs via Stochastic Games"

Artifact for the IJCAI 2024 paper "Solving Long-run Average Reward Robust MDPs via Stochastic Games"

External link: https://github.com/mehrdad76/RMDP-LRA

This repository contains the codebase of the paper titled "Solving Long-run Average Reward Robust MDPs via Stochastic Games".

Dependencies

In order to run the code the following dependencies must be met:

- Python 3 should be installed. We used Python 3.9 to obtain the results in the paper. 
- `Numpy` library should be installed. 
- `Stormpy` library should be installed. 
- `matplotlib` library should be installed. 

Structure and How to run

There are four Python files in the repository.

(i) `StrategyIteration.py` is the backend code, containing the implementation of the RPPI algorithm described in the paper.

(ii) `contamination.py` runs the experiments regarding the contamination model.

(iii) `lake_unichain_priodic.py` runs the experiments regarding the unichain frozen lake model.

(iv) `lake_multichain_priodic.py` runs the experiments regarding the multichain frozen lake model.

The results folder contains the results we obtained by running the experiments (also in the paper).

To run each of the experiments, simply execute: python3 [experiment file] where [experiment file] is one of (ii), (iii) or (iv) from the above list.