SYS 616 or CS 616 In-depth study of a few major areas historically considered to be part of artificial intelligence. Cross-listed as CS 716. Applications are drawn from water resources, environmental, industrial and other engineering areas. Topics discussed and papers reviewed are selected at the first meeting. Students are expected to read every paper before it is presented.
Class size is limited.
The process of stochastic model building including model identification, estimation, and model diagnostic checking. Topics determined by student and faculty interests. Topics may include model and simulation theory, validation, experiment design, output analysis, variance-reduction techniques, simulation optimization, perturbation analysis, parallel and distributed simulation, intelligent simulation systems, animation and output visualization. Course links material from optimization, intelligence systems, and complexity analysis. Formal development of the methods and complete discussion of applications, theoretical properties, and evaluation.