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Computer Simulation - Syllabus

CSE 40239/60239
Computer Simulation
Spring Semester 2006
Time: Tues-Thurs 2:00-3:15
Location: 311 Debartolo

Instructor: Greg Madey
Email:
gmadey@nd.edu
Phone: 574-631-8752
Office: 350 Fitzpatrick Hall

TA: Ryan Kennedy
Email:
rkenned1@nd.edu
Office: 206 Cushing

Computer techniques for simulating the behavior of physical, biological, engineering and social systems, including both natural and artificial systems. Applications include scientific inquiry, engineering design, manufacturing planning, training, entertainment, and games.  This semester will focus on the modeling of biological systems

Texts:

 Discrete-Event System Simulation (4rd edition), Jerry Banks, John Carson, Barry
 L. Nelson, David Nicol, Prentice Hall, 2005, ISBN: 0131446797, 624 pages

 Individual-based Modeling and Ecology, Volker Grimm, Steven F. Railsback,
 Princeton University Press, 2005, ISBN: 069109666X, 480 pages

Reference:

 Turtles, Termites, and Traffic Jams: Explorations in Massively Parallel
Microworlds, M. Resnick,  MIT Press, 2000

Course Goals

 1) The student will learn the theory of computer simulation and modeling, how it is used, and methods and tools for simulation and modeling.

 2) The student will learn and be able to model phenomena using discrete and continuous probability distributions, and elements from queueing theory.

 3) The student will learn the techniques of pseudo-random number generation, how to test and evaluate generators in a given application, and how to use those generators to model phenomena of interest.

 4) The student learn to design a computer simulation, conduct input modeling, verification, validation, and output analysis.

 5) The student will apply knowledge and skills learned on at least one large collaborative modeling and simulation project.
:
 Simulations will be built using the programming languages such as C/C++ or Java, using libraries such as CSIM, SWARM, or RePast, tools including MatLab/SimuLink and Mathematica, and packages such as Starlogo, Arena, NetLogo, Powersim, Vensim, and Stella.

Topics (not necesarily in the following order)                                                       Lectures

Introduction to computer simulation and modeling, role in engineering design and scientific discovery, types of simulations, general principles, software

4

Mathematical and statistical models, discrete distributions, continuous distributions, Poisson processes, empirical distributions

3

Random number generation, types of pseudo-random number generators, tests of random number generators

3

Random variate generation

2

Input modeling, simulation design, experimental design

2

Verification and validation

2

Output analysis, interpretation of results, visualization

4

Special topics

2

Biological projects

6

Prerequisites: One course in programming (or the equivalent) and one course (or the equivalent) in probability/statistics theory

Computer Usage: Course content will be project driven. Many programs will be assigned. At least one large project will be assigned requiring the preparation of research paper.

Grading:

Programming assignments 35%
Exams (2): 20%
Final exam: 20%
Class presentations and particiaption 5%

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