Taylor, S.J.E.; Macal, C.M.; Matta, A.; Rabe, M.; Sanchez,S.M.; Shao, G.: Enhancing Digital Twins with Advances in Simulation and Artificial Intelligence: Opportunities and Challenges. In: Corlu, C.G.; Hunter, S.R..; Lam, H.; Onggo, B.S.; Shortle, J.; Biller, B. (Hrsg.): Proceedings of the 2023 Winter Simulation Conference. Piscataway, NJ: IEEE 2023, S. 3296-3310.

Simulations are used to investigate physical systems. A digital twin goes beyond this by connecting a simulation with the physical system with the purpose of analyzing and controlling that system in real-time. In the past 5 years there has been a substantial increase in research into Simulation and Artificial Intelligence (AI). The combination of Simulation with AI presents many possible innovations. Similarly, combining AI with Simulation presents further possibilities including approaches to developing trustworthy and explainable AI methods, solutions to problems arising from sparce or no data and better methods for time series analysis. Given the progress that has been made in Digital Twins and Simulation and AI, what opportunities are there from combining these two exciting research areas? What challenges need to be overcome to achieve these? This article discusses these from the perspectives of six leading members of the Modeling & Simulation community.