Simulation

Catalog description

This course explores how complex systems can be modeled and simulated using computer programs with an emphasis on models that are discrete, dynamic, and stochastic. Students will formulate models using both event-oriented and process-oriented modeling paradigms, implement the models in code, run computational experiments to gather output, and analyze and interpret the results. Topics include Monte Carlo simulation, discrete-event simulation, probability and random variables, pseudorandom number generation, and output analysis. Prerequisite: CS 220 ; MTH 207 . Offered Occasionally.