DEVS Copilot: Towards Generative AI-Assisted Formal Simulation Modelling based on Large Language Models
Tobias Carreira-Munich, Valentín Paz-Marcolla, Rodrigo Castro · 2024
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.