Artificial Intelligence and Modeling & Simulation: An Overview

Abstract:Artificial intelligence (AI) and Modeling & Simulation (M&S) are increasingly intertwined, reflecting converging research needs across both communities, rapid technological advances such as the rise of generative AI, and the growing availability of data and computational resources. This report provides a structured overview of the intersections of AI and M&S. The relationship goes both ways: AI can support, augment, or even replace components of simulation studies, while simulations can serve as data generators, training environments, and evaluation platforms for AI. We organize this landscape along the stages of M&S from model specification and input modeling to execution, experimentation, verification and validation, and output analysis. Selected studies at each stage illustrates how techniques such as Large Language Models have reshaped simulation practices, while highlighting limitations and open challenges. This report also provides a conceptual roadmap that helps readers navigate a rapidly changing ecosystem.

Software Engineering (cs.SE); Artificial Intelligence (cs.AI)

arXiv:2608.00366 [cs.SE]

(or arXiv:2608.00366v1 [cs.SE] for this version)

https://doi.org/10.48550/arXiv.2608.00366 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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