SYS 3060

Stochastic Decision Models

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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.


  • Robert Riggs

     Rating

    3.67

     Difficulty

    3.50

     GPA

    3.77

     Sections

    Last Taught

    Spring 2025

  • Roman Krzysztofowicz

     Rating

    2.24

     Difficulty

    4.37

     GPA

    3.09

     Sections

    Last Taught

    Spring 2020

  • Quanquan Gu

     Rating

     Difficulty

     GPA

    3.31

     Sections

    Last Taught

    Spring 2016

  • Aram Bahrini

     Rating

     Difficulty

     GPA

     Sections

    Last Taught

    Spring 2022