CS486/686 Winter 2026 - Introduction to Artificial Intelligence

This is a tentative schedule only. As the course progresses, the schedule will be adjusted.

[RN3] 3rd edition of Artificial Intelligence: A Modern Approach by Russell and Norvig

[P] 2nd edition of Causality: Models, Reasoning and Inference by Pearl

[ZLLS] Aston Zhang, Zack C. Lipton, Mu Li, Alex J. Smola, Dive into Deep Learning (forthcoming)

Lecture	Date	Topic	Readings (textbooks)
1	Jan 6	Introduction to Artificial Intelligence (slides)	[RN3] Chapt. 1 and 2
2	Jan 8	Uninformed Search (slides)	[RN3] Sect. 3.1-3.4
3	Jan 13	Informed Search	[RN3] Sec. 3.5, 3.6
4	Jan 15	Constraint Satisfaction	[RN3] Sec 6.1-6.3
5	Jan 20	Uncertainty	[RN3] Sect. 13.1-13.5
6	Jan 22	Bayesian Networks	[RN3] Sections 14.1, 14.2, 14.4
Jan 23	Assignment 1 due (11:59 pm)
7	Jan 27	Bayesian Networks	[RN3] Sections 14.1, 14.2, 14.4
8	Jan 29	Causal Inference	[P] Chapter 1
9	Feb 3	Intro to ML and Decision Tree Learning	[RN3] Sec 18.1-18.4
10	Feb 5	Statistical Learning	[RN3] Sec 20.1-20.2
Feb 6	Assignment 2 due (11:59 pm)
11	Feb 10	Neural Networks	[RN3] Sec 18.7, [ZLLS] Chapter 5
12	Feb 12	Deep Neural Networks	[ZLLS] Chapter 5
Feb 12	Midterm (7:30 - 8:50 pm in M3-1006)
13	Feb 24	Sequence modeling, HMMs, RNNs	[RN3] Sec 15.1-15.3, 15.5
14	Feb 26	Attention and Transformers
Feb 27	Project proposal due at 11:59 pm (CS686 only)
15	Mar 3	Markov Decision Processes
16	Mar 5	Intro to Reinforcement Learning
Mar 6	Assignment 3 due (11:59 pm)
17	Mar 10	Deep Reinforcement Learning
18	Mar 12	Policy Gradient
19	Mar 17	Reinforcement Learning from Human Feedback
20	Mar 19	Test time inference and reasoning
Mar 20	Assignment 4 due (11:59 pm)
21	Mar 24	Game Theory
22	Mar 26	Multi-agent RL
23	Mar 31	Agentic Frameworks
24	Apr 2	Course Recap
April 10	Project report due at 11:59 pm (CS686 only)