SYS 3060

Stochastic Decision Models

Course Description

Pre-Requisite(s): APMA 3100 or MATH 3100

This is an introductory course on modeling probabilistic systems. The emphasis will be on model formulation and probabilistic analysis. Topics to be covered include general stochastic processes, discrete and continuous time Markov chains, the Poisson Process, Non-Stationary Poisson Processes, Markov Decision Processes, Queueing Theory, and other selected topics.


Looks like this course isn't being taught this semester.

Sort by "All" in the top right to see previous semesters.