CSE 471: Introduction to Artificial Intelligence
Class: M/W, 1:30--2:45PM
Office Hours: ASU Sync, M/W, 3:15--4:15PM
TA: Akkamahadevi Hanni
| Course home | Syllabus | Schedule | Student Projects |
Subject to change. Check back frequently for updates.
Last updated: Jan 10, 2022
| Date | Topics | Lecture Notes |
Reading/Project Assignments | Deadlines | Important Dates |
| M. 01/10 | Course introduction. | Lecture Slides | Recommended: R&N, Third Edition, Chapter 1 | ||
| W. 01/12 | Rational agent. | Lecture Slides | Required: R&N, Third Edition, Chapter 2 | ||
| M. 01/17 | Holiday observed; class excused | Lecture Slides | |||
| W. 01/19 | Search. | Lecture Slides | Required: R&N, Third Edition, Chapter 3.1--3.4 | ||
| M. 01/24 | Uninformed search. | Lecture Slides | Required: R&N, Third Edition, Chapter 3.1--3.4 | ||
| W. 01/26 | Informed search. | Lecture Slides | Required: R&N, Third Edition, Chapter 3.5--3.6 | ||
| M. 01/31 | Adversarial search. | Lecture Slides | Required: R&N, Third Edition, Chapter 5 | ||
| W. 02/02 | Adversarial search (cont) | Lecture Slides | Required: R&N, Third Edition, Chapter 5 | ||
| M. 02/07 | General games | Lecture Slides | Required: R&N, Third Edition, Chapter 5, 16 | ||
| W. 02/09 | Logic Agents | Lecture Slides | Required: R&N, Third Edition, Chapter 7 | ||
| M. 02/14 | Logic Agents (cont.) | Lecture Slides | Required: R&N, Third Edition, Chapter 7 | ||
| W. 02/16 | Logic Agents (cont.) | Lecture Slides | Required: R&N, Third Edition, Chapter 7 | ||
| M. 02/21 | First-order logic | Lecture Slides | Required: R&N, Third Edition, Chapter 9 | ||
| W. 02/23 | Markov Decision Process | Lecture Slides | Required: R&N, Third Edition, Chapter 17.1-2 | ||
| M. 02/28 | Markov Decision Process (cont.) | Lecture Slides | Required: RN, Third Edition, Chapter 17.1-2 | ||
| W. 03/02 | Markov Decision Process (cont.) | Lecture Slides | Required: RN, Third Edition, Chapter 17.1-2 | ||
| M. 03/07 | Spring break | ||||
| W. 03/09 | Spring break | ||||
| M. 03/14 | Reinforcement Learning | Lecture Slides | Required: RN, Third Edition, Chapter 21.1-3 | ||
| W. 03/16 | Reinforcement Learning (cont) | Lecture Slides | Required: RN, Third Edition, Chapter 21.4-5 | ||
| M. 03/21 | Reinforcement Learning (cont) | Lecture Slides | Required: RN, Third Edition, Chapter 21.4-5 | ||
| W. 03/23 | Probabilistic inference | Lecture Slides | Required: RN, Third Edition, Chapter 13 | ||
| M. 03/28 | Bayesian Network | Lecture Slides | Required: RN, Third Edition, Chapter 14 | ||
| W. 03/30 | Bayesian Network (cont) | Lecture Slides | Required: RN, Third Edition, Chapter 14 | ||
| M. 04/04 | Hidden Markov Model | Lecture Slides | Required: RN, Third Edition, Chapter 15 | ||
| W. 04/06 | Particle Filters | Lecture Slides | Required: RN, Third Edition, Chapter 15 | ||
| M. 04/11 | Decision Networks | Lecture Slides | Required: RN, Third Edition, Chapter 16 | ||
| W. 04/13 | Naive Bayes | Lecture Slides | Required: RN, Third Edition, Chapter 20 | ||
| M. 04/18 | Perceptron | Lecture Slides | Required: RN, Third Edition, Chapter 18 | ||
| W. 04/20 | Logistic Regression | Lecture Slides | Required: RN, Third Edition, Chapter 18 | ||
| M. 04/25 | Neural Networks | Lecture Slides | Required: RN, Third Edition, Chapter 18 | ||
| W. 04/27 | TBD | Lecture Slides |