Simulation and Artificial Intelligence. 3 credits

Catalog description

Advanced topics and recent developments in stochastic simulation methodology and the intersection with artificial intelligence, featuring interdisciplinary applications in energy systems, financial engineering, health care, manufacturing, transportation, etc. Topics include simulation multivariate input modeling and uncertainty quantification, surrogate modeling with Gaussian process, simulation experiment design, simulation risk analytics, simulation optimization, digital twin-based decision making, optimal sampling policies for reinforcement learning, Monte Carlo tree search, and active learning. Offered by Systems Engr & Operations Rsch . May not be repeated for credit. Equivalent to SYST 735 .