Towards a Domain-Specific Modelling Environment for Reinforcement Learning

Natalie Sinani, Sahil Salma, Paul Boutot, Sadaf Mustafiz

2025

Abstract

In recent years, machine learning technologies have gained immense popularity and are being used in a wide range of domains. However, due to the complexity associated with machine learning algorithms, it is a challenge to make it user-friendly, easy to understand and apply. In particular, reinforcement learning (RL) applications are especially challenging for users who do not have proficiency in this area. In this paper, we use model-driven engineering (MDE) methods and tools for developing a framework for abstracting RL technologies to improve the learning curve for RL users. Our domain-specific modelling environment for reinforcement learning supports syntax-directed editing, constraint checking, code synthesis, and enables comparative analysis of results generated with multiple RL algorithms. We demonstrate our framework with the use of several reinforcement learning applications.

Paper Citation

in Harvard Style

Sinani N., Salma S., Boutot P. and Mustafiz S. (2025). Towards a Domain-Specific Modelling Environment for Reinforcement Learning. In Proceedings of the 13th International Conference on Model-Based Software and Systems Engineering - Volume 1: MODELSWARD; ISBN 978-989-758-729-0, SciTePress, pages 40-51. DOI: 10.5220/0013123800003896

in Bibtex Style

@conference{modelsward25,
author={Natalie Sinani and Sahil Salma and Paul Boutot and Sadaf Mustafiz},
title={Towards a Domain-Specific Modelling Environment for Reinforcement Learning},
booktitle={Proceedings of the 13th International Conference on Model-Based Software and Systems Engineering - Volume 1: MODELSWARD},
year={2025},
pages={40-51},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013123800003896},
isbn={978-989-758-729-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Model-Based Software and Systems Engineering - Volume 1: MODELSWARD
TI - Towards a Domain-Specific Modelling Environment for Reinforcement Learning
SN - 978-989-758-729-0
AU - Sinani N.
AU - Salma S.
AU - Boutot P.
AU - Mustafiz S.
PY - 2025
SP - 40
EP - 51
DO - 10.5220/0013123800003896
PB - SciTePress