Simon Fraser University
Engaging the World

Course Outlines

Fall 2019 - CMPT 983 G100

Special Topics in Artificial Intelligence (3)

Class Number: 9705

Delivery Method: In Person

Overview

  • Course Times + Location:

    Sep 3 – Dec 2, 2019: Mon, 10:30 a.m.–12:20 p.m.
    Burnaby

    Sep 3 – Dec 2, 2019: Wed, 10:30–11:20 a.m.
    Burnaby

Description

COURSE DETAILS:

This course introduces fundamental concepts in robotics and related fields, including analytical methods for decision making, and machine learning in the context of robotics. Topics include modeling and simulation of robotic systems, optimization, optimal control, robotic safety, reinforcement learning, and robotic perception. Applications of the material include unmanned aerial vehicles and self-driving cars.

Topics

  • Modeling and simulation
  • Optimization
  • Optimal control
  • Robotic safety
  • Reinforcement learning
  • Robotic perception

Grading

NOTES:

The course grade will be based on homework assignments, a project, and exams.

Materials

RECOMMENDED READING:

Introduction to Autonomous Mobile Robots,
R. Siegwart, I. R. Nourbakhsh, and D. Scaramuzza,
MIT Press,

ISBN: 9780262015356

Planning Algorithms
S. M. LaValle
Cambridge University Press
ISBN: 9780521862059

Convex Optimization
S. Boyd and L. Vandenberghe
Cambridge
ISBN: 9780521833783

Dynamic Programming and Optimal Control
D. P. Bertsekas
Athena Scientific
ISBN: 9781886529434

Reinforcement Learning: An Introduction
R. S. Sutton and A. G. Barto
MIT
ISBN: 9780262039246

Graduate Studies Notes:

Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.

Registrar Notes:

SFU’s Academic Integrity web site http://www.sfu.ca/students/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