AI and Simulation Intersections: A Structured Overview

A recent publication on arXiv (ID 2608.00366) offers a detailed examination of the connections between artificial intelligence (AI) and Modeling & Simulation (M&S). It emphasizes the reciprocal nature of their relationship: AI can enhance, support, or even substitute elements of simulation studies, whereas simulations provide data generation, training settings, and evaluation frameworks for AI. The report categorizes the M&S process into stages, including model specification, input modeling, execution, experimentation, verification and validation, and output analysis. Case studies at each phase demonstrate how innovations like Large Language Models have transformed simulation methodologies, while also addressing existing limitations and challenges. The findings underscore the shared research interests of both fields, the swift advancements in technology, particularly generative AI, and the increasing access to data and computational power. The complete document is accessible on arXiv.