CMPUT 261 (Winter 2024)

Intro to Artificial Intelligence

Schedule

This schedule is subject to change as the semester progresses, but it will be kept up to date. Slides are linked from the lecture title. They will be made available on the day of the lecture.

wk Date Topic Readings & Milestones
1 Tue, Jan 9 Introduction: Course Overview
no labs this week
1 Thu, Jan 11 Search: Graph Search P&M §3.1–3.4
no labs this week
2 Tue, Jan 16 Search: Uninformed Search P&M §3.5
2 Thu, Jan 18 Search: Heuristic Search 1 P&M §3.6
Assignment 1 released
Add/drop deadline: Jan 19
3 Tue, Jan 23 Search: Heuristic Search 2 P&M §3.7–3.8
3 Thu, Jan 25 Uncertainty: Probability Theory P&M §8.1
4 Tue, Jan 30 Uncertainty: Conditional Independence P&M §8.2
4 Thu, Feb 1 Uncertainty: Belief Networks P&M §8.3
Assignment 1 due
5 Tue, Feb 6 Uncertainty: Inference in Belief Networks P&M §8.4
Assignment 2 released
5 Thu, Feb 8 Supervised Learning: Introduction & Framework P&M §7.1–7.2
6 Tue, Feb 13 Supervised Learning: Calculus Refresher P §B.3–B.3.4, §B.5
6 Thu, Feb 15 Supervised Learning: Linear Models P&M §7.3
  Tue, Feb 20 reading week, no class  
  Thu, Feb 22 reading week, no class  
7 Tue, Feb 27 Supervised Learning: Overfitting P&M §7.4
7 Thu, Feb 29 Supervised Learning: Bayesian Inference P&M §10.4, §8.6
Assignment 2 due
8 Tue, Mar 5 MIDTERM  
8 Thu, Mar 7 Deep Learning: Neural Networks P §3.1–3.6
9 Tue, Mar 12 Deep Learning: Training Neural Networks P §7.1–7.4.1
Assignment 3 released
9 Thu, Mar 14 Deep Learning: Image Data P §10.1–10.4.1, §10.5
10 Tue, Mar 19 Deep Learning: Sequence Data P §12.1–12.2, §12.4, §12.6
10 Thu, Mar 21 Reinforcement Learning: Markov Decision Processes S&B §3.0–3.5
11 Tue, Mar 26 Reinforcement Learning: Optimality and Dynamic Programming S&B §3.6, §4.0–4.4
Assignment 3 due
11 Wed, Mar 27 Wednesday, no class Assignment 3 due
11 Thu, Mar 28 Reinforcement Learning: Monte Carlo Prediction & Control S&B §5.0–5.5, §5.7
Assignment 4 released
12 Tue, Apr 2 Reinforcement Learning: TD-Learning Prediction & Control S&B §6.0–6.5
12 Thu, Apr 4 Reinforcement Learning: Function Approximation & Policy Gradient Methods S&B §9.0–9.5.4, §13.0–13.3
Withdrawal deadline: Apr 5
13 Tue, Apr 9 Guest lecture: Goal Recognition Design  
13 Thu, Apr 11 Multiagent Systems: Game Theory for Single Interactions S&LB §3.0–3.3.2
Assignment 4 due
  Tue, Apr 23
9:00am
FINAL EXAM ED 2-115
(usual lecture hall)