CSE 471: Intro to Artificial Intelligence
Class: ISTBX101, T/Th, 3:00--4:15PM
Office Hours: T/Th, 1:30--2:30PM
Office Hours (TA: Qi Lin): TBD
Office Hours (Grader: Kevin Vora): TBD
| Course home | Syllabus | Schedule | Student Projects |
Subject to change. Check back frequently for updates.
Last updated: Aug. 18, 2026
| Date | Topics | Lecture Notes |
Reading/Project Assignments | Deadlines | Important Dates |
| Th. 08/20 | Course introduction. | Lecture Slides | Recommended: R&N, Third Edition, Chapter 1 | ||
| T. 08/25 | Rational agent. | Lecture Slides | Required: R&N, Third Edition, Chapter 2 | ||
| Th. 08/27 | Search. | Lecture Slides | Required: R&N, Third Edition, Chapter 3.1--3.4 | ||
| T. 09/01 | Uninformed search. | Lecture Slides | Required: R&N, Third Edition, Chapter 3.1--3.4 | ||
| Th. 09/03 | Informed search. | Lecture Slides | Required: R&N, Third Edition, Chapter 3.5--3.6 | ||
| T. 09/08 | Adversarial search. | Lecture Slides | Required: R&N, Third Edition, Chapter 5 | ||
| Th. 09/10 | Adversarial search (cont) | Lecture Slides | Required: R&N, Third Edition, Chapter 5 | ||
| T. 09/15 | General games | Lecture Slides | Required: R&N, Third Edition, Chapter 5, 16 | ||
| Th. 09/17 | Logic Agents | Lecture Slides | Required: R&N, Third Edition, Chapter 7 | ||
| T. 09/22 | Logic Agents (cont.) | Lecture Slides | Required: R&N, Third Edition, Chapter 7 | ||
| Th. 09/24 | Logic Agents (cont.) | Lecture Slides | Required: R&N, Third Edition, Chapter 7 | ||
| T. 09/29 | First-order logic | Lecture Slides | Required: R&N, Third Edition, Chapter 9 | ||
| Th. 10/01 | Markov Decision Process | Lecture Slides | Required: R&N, Third Edition, Chapter 17.1-2 | ||
| T. 10/06 | Markov Decision Process (cont.) | Lecture Slides | Required: RN, Third Edition, Chapter 17.1-2 | ||
| Th. 10/08 | Markov Decision Process (cont.) | Lecture Slides | Required: RN, Third Edition, Chapter 17.1-2 | ||
| T. 10/13 | Fall break; class excused | Lecture Slides | |||
| Th. 10/15 | Reinforcement Learning | Lecture Slides | Required: RN, Third Edition, Chapter 21.1-3 | ||
| T. 10/20 | Reinforcement Learning (cont) | Lecture Slides | Required: RN, Third Edition, Chapter 21.4-5 | ||
| Th. 10/22 | Reinforcement Learning (cont) | Lecture Slides | Required: RN, Third Edition, Chapter 21.4-5 | ||
| T. 10/27 | Probabilistic inference | Lecture Slides | Required: RN, Third Edition, Chapter 13 | ||
| Th. 10/29 | Bayesian Network | Lecture Slides | Required: RN, Third Edition, Chapter 14 | ||
| T. 11/03 | Bayesian Network (cont) | Lecture Slides | Required: RN, Third Edition, Chapter 14 | ||
| Th. 11/05 | Hidden Markov Model | Lecture Slides | Required: RN, Third Edition, Chapter 15 | ||
| T. 11/10 | Particle Filters | Lecture Slides | Required: RN, Third Edition, Chapter 15 | ||
| Th. 11/12 | Veterans day; class excused | Lecture Slides | |||
| T. 11/17 | Decision Networks | Lecture Slides | Required: RN, Third Edition, Chapter 16 | ||
| Th. 11/19 | Naive Bayes | Lecture Slides | Required: RN, Third Edition, Chapter 20 | ||
| T. 11/24 | Perceptron | Lecture Slides | Required: RN, Third Edition, Chapter 18 | ||
| Th. 11/26 | Thanksgiving; class excused | Lecture Slides | |||
| T. 12/01 | Logistic Regression | Lecture Slides | Required: RN, Third Edition, Chapter 18 | ||
| Th. 12/03 | Neural Networks | Lecture Slides | Required: RN, Third Edition, Chapter 18 |