Artificial Intelligence Survey

CMPT 310, Spring 2020

Instructor: Yağız Aksoy

TA’s: Matthew Lynn and Yiqi Yan

Lectures:
Mon, Wed, Fri, 15:30-16:20, SSCK 9500

Office hours:
Yağız: Friday 4:30pm, following the lecture (tentative)
Matthew and Yiqi: TBA

Prerequisites:
(i) CMPT 225
(ii) MACM 101 or (ENSC 251 and ENSC 252)

Announcements, Lecture Notes, Questions and Discussion

Our main venue for communication is Piazza .

You can also find the course on Coursys .

Textbook

Peter Norvig and Stuart J. Russell, Artificial Intelligence: A Modern Approach, 3rd Ed.

Programming assignments

Programming Assignment 1: Search. Due Feb 9, by midnight.

There will be 4 programming assignments, TBA here and on Coursys. Tentative due dates: Early Feb, late Feb, mid March, early April.

Lecture slides

Lecture slides will be distributed through Piazza in a more timely manner.

Tentative schedule

  • Search
    • Depth-first, breadth-first, informed
    • Games and adversarial search
    • Constraint satisfaction problems
  • Probability
    • Bayesian networks
    • Hidden Markov models
  • Machine learning
    • Decision trees
    • Neural networks
    • Training and evaluation
  • Advanced applications (NLP, Computer Vision)

Grading

Programming assignments - 4 x 6.25% = 25%
Midterm (March 13, during lecture) - 25%
Final (April 22, 8:30am) - 50%
Participation in Piazza discussions - up to 5% bonus

Late Policy

You have 4 days of penalty-free late submission for the whole semester, use them wisely. After your free 4 days, late submissions will receive a 33% penalty per day. Submitting 1 hour or 23 hours after the deadline both count as 1-day late submission.

Academic Integrity

You are encouraged to talk about and discuss coding assignments with your class-mates. You are allowed to use existing code/library (e.g., optimization library or vector calculus library), in which case, you have to explicitly describe it in your report. Besides the above case, every single line of code must be written by you, and you are not allowed to copy from other sources. Writing the code by exactly or closely following existing code is not technically copy-and-paste, but is also considered to be copy-and-paste. Use your fair judgement. You know what is good and bad. When in doubt, consult the instructor. You are expected to maintain the highest standards of academic integrity and refrain from the forms of misconduct.