How can we use computers to design systems and, more generally, make decisions, in the face of complexity and uncertainty?
Simulation techniques apply the power of the computer to study complex stochastic systems when analytical or numerical techniques do not suffice. It is the most frequently used methodology for the design and evaluation of computer, telecommunication, manufacturing, healthcare, financial, and transportation systems, to name just a few application areas. Simulation is an interdisciplinary subject, incorporating ideas and techniques from computer science, probability, statistics, optimization, and number theory. Simulation models, which embody deep domain expertise, can effectively complement machine-learning approaches.
This course will provide a hands-on introduction into this fascinating and useful subject.
Class Meetings: TTh 1:00-2:15pm in CS 140. Due to the suspension of live class meetings, the class will meet via ZOOM until further notice. See Piazza for ZOOM link details.
Instructor: Prof. Peter J. Haas
Contact: phaas@cs.umass.edu
Office Hours: Tues 5-6pm and Wed 2-3pm in CS 204. Until further notice, office hours will be held via ZOOM; see Piazza for details
Teaching Assistant: Cen Wang
Contact: cenwang@umass.edu
Office Hours: Mon 4:30-5:30pm and Thur 2:30-3:30pm in CS 207. Until further notice, office hours will be held via ZOOM
Grader: Aditya Vikram Agarwal
Contact: adityavikram@umass.edu
Required textbook: A. M. Law, Simulation Modeling and Analysis, 5th Edition, 2015, McGraw Hill. ISBN 9780073401324.
(Very) optional textbook: P. J. Haas, Stochastic Petri Nets: Modelling Power and Limit Theorems, 2001, Springer.
Last modified 31 March 2020