Summer 2018 - ENSC 482 D100
Introduction to Decision Making in Engineering (4)
Class Number: 1128
Delivery Method: In Person
Overview
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Course Times + Location:
May 7 – Aug 3, 2018: Mon, Wed, 10:30 a.m.–12:20 p.m.
Burnaby -
Exam Times + Location:
Aug 13, 2018
Mon, 8:30–11:30 a.m.
Burnaby
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Instructor:
Shahram Payandeh
payandeh@sfu.ca
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Prerequisites:
MATH 232, MACM 316, (ENSC 280 or MSE 210 or PHYS 231), and a minimum of 80 units.
Description
CALENDAR DESCRIPTION:
Covers topics from decision theory, pattern classification and optimization theory. In addition, it introduces students to the design and development of interactive decision making tools which can assist designers during the design process.
COURSE DETAILS:
General Description: Scheduling, monitoring, designing are all engineering tasks that require decisionmaking. This course introduces students to tools and methodologies enabling decision making. We will discuss the applicability of these tools at the various stages of the tasks.
Lectures: During lectures, we will review various decision-making tools and methodologies. Sources of these tools will be listed at the end of each topic, as well as further readings from the SFU library. Lecture slides will be e-mailed to the class a week in advance. In addition to the tools and methodologies, the slides
will include various problems where those are applicable. Solutions to these problems are presented during the lectures through student participation. It is highly encouraged that students attend classes to understand and appreciate solution methodologies fully. Exam problems are usually very similar to the issues presented during
classes. Assignments (including programming assignments in C ++ with OpenGL as a solution visualization tool) and quizzes will also be like those problems jointly discussed.
Project: A final group project is for groups of three students to implement decision making based on the tools or methodologies learned. The group project is to be designed and developed in C ++ and OpenGL environments in three stages through consultation with the instructor. A portion of the total project marks will be assigned at the completion of each step. The first stage is the definition of the theme of the project. Deliverable for this stage is an extended abstract. Due date is the middle of the semester. The second stage is a progress report and demonstration of the implementation. The due date for this stage is the last week of the term. The final stage is the detailed deliverable and the final report. The due date of the final deliverable is two days before the final exam. A conference style presentation will be scheduled after the date of final exam.
COURSE OUTLINE
Summer of 2018
Weeks 1-3
1. Decision Theory
1.1 Introduction
1.2 Classification
1.3 Decision Matrix
1.4 Utility
Weeks 3-5
2. Game Theory
2.1 Introduction and Strategy classifications
2.2 Nash Equilibrium
2.3 Mixed Strategies Nash Equilibrium
2.4 Examples
Weeks 5-6
3. Statistics and Probability Concepts in Decision Making
3.1 Correlation and Regression
3.2 Bayes’ Theorem
3.3 Bayesian Network
3.4 Markov Chain
Weeks 6-8
4. Graph Theory and Decision Supports
4.1 Definitions and Representations
4.2 Binary Search Tree and Greedy Algorithm
4.3 Graph Search
4.4 Regression Tree
4.5 Spanning Tree and Shortest path
Weeks 8-10
5. Pattern Classification
5.1 Basic Concepts
5.2 Decision Functions
5.3 Distance Functions
5.4 Likelihood Functions
5.5 Clustering
Weeks 10-13
6. Design Optimization for Decision Supports
6.1 Formulation for Optimum Design
6.2 Graphical Optimization
6.3 Linear Programming
6.4 Simplex Method
Grading
- Assignments 20%
- Project 20%
- Exam 1 20%
- Exam 2 20%
- Exam 3 20%
Registrar Notes:
SFU’s Academic Integrity web site http://students.sfu.ca/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.
Each student is responsible for his or her conduct as it affects the University community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS