Overview

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

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