DEVS Copilot: Towards Generative AI-Assisted Formal Simulation Modelling based on Large Language Models
In this paper we explore to which extent generative AI, in the form of Large Language Models such as GPT-4, can assist in obtaining a correct executable simulation model. The starting point is a high-level description of a system, expressed in natural language, which evolves through a conversational process based on user input, including suggestions for corrections. We introduce a methodology and a tool inspired by the metaphor of a copilot, a form of human-AI teaming strategy well known for its success in programming tasks. We adopt the Discrete Event System Specification (DEVS), a suitable candidate formalism that allows general-purpose simulation models to be specified in a simple yet rigorous modular and hierarchical way. The result is DEVS Copilot, an AI-based prototype that we systematically test in a case study that builds several lighting control systems of increasing complexity. In all cases, DEVS Copilot succeeds at producing correct DEVS simulations.
Authors
- Rodrigo Castro (ORCID: https://orcid.org/0000-0003-4038-5999)
- Tobias Carreira-Munich
- Valentín Paz-Marcolla
Institutions
- Universidad de Buenos Aires (AR)
- Fundación Ciencias Exactas y Naturales (AR)
Publication Details
- Published
- 2024-12-15
- DOI
- https://doi.org/10.1109/wsc63780.2024.10838994
- Citations
- 5
- Primary Topic
- Model-Driven Software Engineering Techniques
- Type
- article
- Field-Weighted Citation Impact
- 2.43