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.

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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
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article

DEVS Copilot: Towards Generative AI-Assisted Formal Simulation Modelling based on Large Language Models

Rodrigo Castro, Tobias Carreira-Munich, Valentín Paz-Marcolla
5 citations
Model-Driven Software Engineering Techniques
2.43
article

DEVS Copilot: Towards Generative AI-Assisted Formal Simulation Modelling based on Large Language Models

Rodrigo Castro, Tobias Carreira-Munich, Valentín Paz-Marcolla
article en
5 citations

Abstract

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.

Universidad de Buenos Aires (AR), Fundación Ciencias Exactas y Naturales (AR)
Openalex Percentile: Top 9%
Model-Driven Software Engineering Techniques
2.43
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