CS 486/686 · Spring 2026

Introduction to Artificial Intelligence

Taught by Yuntian Deng · yuntian@uwaterloo.ca

Section 001: TTh 1:00 PM - 2:20 PM · MC 4021Section 002: TTh 2:30 PM - 3:50 PM · MC 4021Class dates: May 11, 2026 - Aug 5, 2026 Final exam: Aug 7 - 20, 2026 (Exact date set by Registrar (TBA))

Course staff

Instructor. Yuntian Deng · yuntian@uwaterloo.ca

For Piazza-related inquiries, please contact Liliana and cc the instructor. The instructor receives many emails and response time may be slow.

Teaching assistants

Office hours

Office hours start the Week of May 18.

Weekly office hours (Zoom links are one-click; passcodes embedded).
Day Time TA Mode
Monday 1:00 - 2:00 PM Larry Yinxi Li Zoom
Monday 2:00 - 3:00 PM Dake Zhang Zoom
Monday 3:00 - 4:00 PM Yuxuan Li Zoom
Wednesday 1:00 - 2:00 PM Hala Sheta Zoom
Thursday 10:00 - 11:00 AM Henry Lin Zoom
Friday 3:00 - 4:00 PM Bihui Jin In person · DC 2555

Communication

  • All class-wide communication happens on the Piazza discussion board.
  • Public posts (can be anonymous) are the preferred way to ask questions about course material - other students can help and instructors can read/reply.
  • Private posts (to instructors only) are for anything containing solution snippets or private questions.
  • For Chrysalis-specific issues, make a private Piazza post addressed to Prashanth Arun and Robert Cai.
  • Course materials and assignments live on LEARN, not Piazza.
  • Email yuntian@uwaterloo.ca only in exceptional cases where you need to reach the instructor directly.

Course description

This course provides an introduction to the field of artificial intelligence. Topics include search algorithms, game playing, knowledge representation and reasoning, uncertainty and probabilistic reasoning, machine learning, neural networks, and reinforcement learning.

Assessment

CS 486 (undergrad)

  • Assignments (3, individually)30%
  • Chat assignments with Chrysalis (10, 2% each)20%
  • Written final exam (must pass to pass the course)50%
  • Optional project+10% bonus

CS 686 (graduate)

  • Assignments (3, individually)30%
  • Project (individually or in groups of up to 3)30%
  • Written final exam40%

CS486 students must pass the final exam to pass the course. Dates for the three assignments are announced as the term progresses.

Chat assignments with Chrysalis

Ten chat assignments, 2% each. In each one you teach Chrysalis what you learned in the lecture by answering a set of questions in a chat interface. Grading is based on participation - you get full marks for each question you genuinely attempt, regardless of whether the answer is correct. Marks are only deducted for skipping questions or not engaging.

How to sign up

  1. Open https://andromeda-208.cs.uwaterloo.ca (hosted on university machines for data security). Bookmark it - you'll use it all term.
  2. Create an account with your WatIAM @uwaterloo.ca email. Do not use the friendly alias (e.g. firstname.lastname@uwaterloo.ca) - we won't be able to link your usage to your Quest ID.
  3. Click the verification link in the email Chrysalis sends you. Once you sign in, you should be added to "CS 486/686" automatically. If you don't see the course on your dashboard, make a private Piazza post.

Schedule

10 chat assignments. Deadlines are 11:59 PM Waterloo time.
# Released Due Notes
Chat 1 Thu May 14 Tue May 26 Deadline extended one-time (originally Tue May 19) so students still finalizing enrollment can participate.
Chat 2 Thu May 21 Thu May 28 Deadline extended two days (originally Tue May 26) to give students more time on the heavier L3 + L4 material.
Chat 3 Thu May 28 Tue Jun 2
Chat 4 Thu Jun 4 Tue Jun 9
Chat 5 Thu Jun 11 Tue Jun 16
Chat 6 Thu Jun 18 Tue Jun 23
Chat 7 Thu Jun 25 Tue Jun 30
Chat 8 Thu Jul 2 Tue Jul 7
Chat 9 Thu Jul 9 Tue Jul 14
Chat 10 Thu Jul 16 Tue Jul 21
When do I stop chatting? How are chats actually graded?

Once you've covered every question at least once, you can stop and close the tab - Chrysalis auto-saves your chat. There is no submit button and no fixed stopping point. Chrysalis may circle back and re-ask questions you've already answered; that's normal.

After the deadline, your chat is automatically graded for participation (full marks for each question genuinely attempted). The quality of your answers is also assessed indirectly via a quiz that Chrysalis answers on your behalf - there are no marks for this quiz; it's a self-diagnostic so you can see which concepts to revisit. After the deadline you'll be able to see which quiz questions Chrysalis got right or wrong based on your teaching.

Project

Who and when

  • Required for CS686 students; optional 10% bonus for CS486 students.
  • Individual or groups of up to 3 (group reports must specify each member's responsibility).
  • Proposal due Tue Jul 7. Final report due during the Aug 7-20 exam period (specific date TBA).

Scope

  • Must relate to course content: search, hidden Markov models, reinforcement learning, neural networks, etc.
  • Acceptable shapes: a new AI algorithm, a theoretical analysis of an existing algorithm, a new dataset or benchmark, an empirical evaluation, or a literature survey.
  • The proposal is a 1-page description: problem, background, motivation, proposed methods.
  • The final report needs: problem definition, dataset, algorithm design, experiments, evaluation, conclusion.

Submission

  • Use the standard LaTeX template for the final report.
  • Submit the proposal and the final report on LEARN before each deadline.
  • Code must not be copied from public repositories - any violation is treated as plagiarism.

Submission guidelines

  • Assignments are individual unless otherwise stated.
  • Submit and receive marks through LEARN.
  • No late assignments are accepted.

Readings

Primary text

  • Artificial Intelligence: Foundations of Computational Agents
    David Poole and Alan Mackworth · 2nd edition, Cambridge University Press, 2017
    Read online ·Available online. The online resources and Python programs are recommended.

Secondary readings

Course schedule

The exact schedule is updated as the course progresses. The closest upcoming class is highlighted automatically.

CS 486/686 (Spring 2026) - class meetings, deadlines, and the final-exam window.
Date Lecture Topic Notes
Search
Tue May 12 L1 Introduction to Artificial Intelligence Slides
Thu May 14 L2 Uninformed Search SlidesChat 1 out
Tue May 19 L3 Heuristic Search Slides
Thu May 21 L4 Constraint Satisfaction Problems SlidesChat 2 out
Tue May 26
10:00 - 11:30 AM		 Event Distinguished Lecture by Prof. Kyunghyun Cho (NYU) · DC 1302
Highly recommended - co-inventor of attention (Bahdanau, Cho, Bengio, ICLR 2015) and the GRU.
Tue May 26 L5 Local Search SlidesChat 1 due (extended)
Reasoning under Uncertainty
Thu May 28 L6 Probabilities SlidesChat 2 due (extended)Chat 3 out
Tue Jun 2 L7 Independence and Bayesian Networks I SlidesChat 3 due
Thu Jun 4 L8 Independence and Bayesian Networks II SlidesChat 4 outAssignment 1 release
Tue Jun 9 L9 Variable Elimination Algorithm SlidesChat 4 due
Thu Jun 11 L10 Hidden Markov Models I SlidesChat 5 out
Tue Jun 16 L11 Hidden Markov Models II SlidesChat 5 due
Decision Making
Thu Jun 18 L12 Decision Theory SlidesChat 6 outAssignment 1 due
Tue Jun 23 L13 Markov Decision Processes I SlidesChat 6 due
Thu Jun 25 L14 Value Iteration and Policy Iteration SlidesChat 7 outAssignment 2 release
Tue Jun 30 L15 Reinforcement Learning SlidesChat 7 due
Machine Learning and Deep Learning
Thu Jul 2 L16 Introduction to Machine Learning SlidesChat 8 out
Tue Jul 7 L17 Unsupervised Learning SlidesChat 8 dueProject proposal due (CS686)
Thu Jul 9 L18 Decision Trees SlidesChat 9 outAssignment 2 dueAssignment 3 release
Tue Jul 14 L19 Neural Networks I SlidesChat 9 due
Thu Jul 16 L20 Neural Networks II SlidesChat 10 out
Tue Jul 21 L21 Neural Networks III SlidesChat 10 due
Thu Jul 23 L22 Course Recap Slides
Tue Jul 28 — No class (buffer / review)
Thu Jul 30 — No class
Tue Aug 4 — No class Assignment 3 due
Aug 7 - 20 Exam Final exam period (specific date set by Registrar). Final project report (CS686) due during this period (TBA).

Waitlist

If you can't register for the course, email yuntian@uwaterloo.ca to join the waitlist.

University of Waterloo academic integrity

Expand the standard policy notices (grievance, discipline, appeals, accommodations)

In order to maintain a culture of academic integrity, members of the University of Waterloo community are expected to promote honesty, trust, fairness, respect and responsibility. Check the Office of Academic Integrity's website for more information.

Grievance

A student who believes that a decision affecting some aspect of his/her university life has been unfair or unreasonable may have grounds for initiating a grievance. Read Policy 70 - Student Petitions and Grievances, Section 4. When in doubt please be certain to contact the department's administrative assistant who will provide further assistance.

Discipline

A student is expected to know what constitutes academic integrity, to avoid committing academic offenses, and to take responsibility for his/her actions. A student who is unsure whether an action constitutes an offense, or who needs help in learning how to avoid offenses (e.g., plagiarism, cheating) or about "rules" for group work/collaboration should seek guidance from the course professor, academic advisor, or the Undergraduate Associate Dean. For information on categories of offenses and types of penalties, students should refer to Policy 71 - Student Discipline. For typical penalties check Guidelines for the Assessment of Penalties.

Avoiding academic offenses

Most students are unaware of the line between acceptable and unacceptable academic behaviour, especially when discussing assignments with classmates and using the work of other students. For information on commonly misunderstood academic offenses and how to avoid them, students should refer to the Faculty of Mathematics Cheating and Student Academic Discipline Policy.

Appeals

A decision made or a penalty imposed under Policy 70 (Student Petitions and Grievances) or Policy 71 (Student Discipline) may be appealed if there is a ground. A student who believes he/she has a ground for an appeal should refer to Policy 72 - Student Appeals.

Note for students with disabilities

The AccessAbility Services Office (AAS), located in Needles Hall, Room 1401, collaborates with all academic departments to arrange appropriate accommodations for students with disabilities without compromising the academic integrity of the curriculum. If you require academic accommodations to lessen the impact of your disability, please register with the AAS at the beginning of each academic term.

Last updated: May 21, 2026 Report an issue