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Course description: APMA 1200 serves as an introduction to stochastic processes and stochastic optimization. Topics covered include Markov chains, Poisson processes, renewal processes, martingales, queueing theory, Markov decision processes, dynamic programming, filtering of hidden Markov models, and Brownian motion.
Prerequisites: APMA 1650, 1655 or MATH 1610, or written permission.
Required text: The following textbook is required reading for APMA 1200.
- Markov Chains by James R. Norris. Cambridge University Press, 1997.
Grading policy: The final grade will be based on homework assignments, a take-home midterm exam (see below for dates) and a final exam.
Homework assignments: Homework problems will be handed out on a regular basis. Discussion of homework assignments with other students is encouraged, but what is handed in should be your own work.
|Midterm exam||Tuesday, March 12|
|Final exam||Friday, May 10|
Accommodations: Brown University is committed to full inclusion of all students. Please inform me early in the term if you have a disability or other conditions that might require accommodations or modification of any of these course procedures. You may speak with me after class or during office hours. For more information, please contact Student and Employee Accessibility Services at 401-863-9588 or SEAS@brown.edu.
Students in need of short-term academic advice or support can contact one of the deans in the Dean of the College office.
The syllabus page shows a table-oriented view of the course schedule, and the basics of course grading. You can add any other comments, notes, or thoughts you have about the course structure, course policies or anything else.
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