CSE 571: Artificial Intelligence
Class: COOR L1-74, T/Th, 4:30--5:45PM
Office Hours: BYENG 594, T/Th, 3:00--4:00PM
Office Hours (TA: Ze and Akku): W 2-4PM (BYENG M1-30), M 2-4PM (BYENG M1-30)
| Course home | Syllabus | Schedule | Student Projects |
Subject to change. Check back frequently for updates.
Last updated: Jan 14, 2020
| Date | Topics | Lecture Notes |
Reading/Project Assignments | Deadlines | Important Dates |
| Tu. 01/14 | Course introduction. | Lecture Slides | Recommended: R&N, Third Edition, Chapter 1 | ||
| Th. 01/16 | Rational agent. | Lecture Slides Lecture Notes | Required: R&N, Third Edition, Chapter 2 | ||
| Tu. 01/21 | Agent case study. | Lecture Slides Lecture Notes | Required: R&N, Third Edition, Chapter 2 | ||
| Th. 01/23 | Introduction to planning | Lecture Slides Lecture Notes | Required: R&N, Third Edition, Chapter 3.1-3.2 | ||
| Tu. 01/28 | Uninformed search. | Lecture Slides Lecture Notes | Required: R&N, Third Edition, Chapter 3.1--3.4 | ||
| Th. 01/30 | Informed search. | Lecture Slides Lecture Notes | Required: R&N, Third Edition, Chapter 3.5--3.6 | ||
| Tu. 02/04 | Adversarial search. | Lecture Slides Lecture Notes | Required: R&N, Third Edition, Chapter 5 | ||
| Th. 02/06 | Adversarial search (cont). | Lecture Slides Lecture Notes | Required: R&N, Third Edition, Chapter 5 | ||
| Tu. 02/11 | Special topic: D* Lite. | Additional reading | |||
| Th. 02/13 | Games | Lecture Slides Lecture Notes | Required: R&N, Third Edition, Chapter 5 | ||
| Tu. 02/18 | Logic Agents | Lecture Slides Lecture Notes | Required: R&N, Third Edition, Chapter 7 | ||
| Th. 02/20 | Logic Agents (cont.) | Lecture Slides Lecture Notes | Required: R&N, Third Edition, Chapter 7 | ||
| Tu. 02/25 | Logic Inference | Lecture Slides Lecture Notes | Required: R&N, Third Edition, Chapter 7 | ||
| Th. 02/27 | Special topic: Dangerous AI | Additional reading | |||
| Tu. 03/03 | Logic Inference | Lecture Slides Lecture Notes | Required: R&N, Third Edition, Chapter 7 | ||
| Th. 03/05 | First-order logic | Lecture Slides Lecture Notes | Required: R&N, Third Edition, Chapter 8 | ||
| Th. 03/10 | Spring break | ||||
| Th. 03/12 | Spring break | ||||
| Tu. 03/17 | Markov Decision Process | Lecture Slides | Required: R&N, Third Edition, Chapter 17.1-2 | ||
| Th. 03/19 | Value Iteration | Lecture Slides | Required: RN, Third Edition, Chapter 17.1-2 | ||
| Tue. 03/24 | Policy Evaluation and Iteration | Lecture Slides | Required: RN, Third Edition, Chapter 17.3 | ||
| Th. 03/26 | MDP example discussion | Lecture Slides | Required: RN, Third Edition, Chapter 17.1-3 | ||
| Tu. 03/31 | Reinforcement Learning | Lecture Slides | Required: RN, Third Edition, Chapter 21.1-3 | ||
| Th. 04/02 | Reinforcement Learning II | Lecture Slides | Required: RN, Third Edition, Chapter 21.1-3 | ||
| Tu. 04/07 | Reinforcement Learning III | Lecture Slides | Required: RN, Third Edition, Chapter 21.1-3 | ||
| Th. 04/09 | Reinforcement Learning IV | Lecture Slides | Required: RN, Third Edition, Chapter 21.4-5 | ||
| Tu. 04/14 | Probability basics | Lecture Slides | Required: RN, Third Edition, Chapter 13 | ||
| Th. 04/16 | Bayesian network | Lecture Slides | Required: RN, Third Edition, Chapter 14.1-2 | ||
| Tu. 04/21 | Bayesian network II | Lecture Slides | Required: RN, Third Edition, Chapter 14.1-2 | ||
| Th. 04/23 | Bayesian network III | Lecture Slides | Required: RN, Third Edition, Chapter 14.1-2 | ||
| Tu. 04/28 | Machine learning | Lecture Slides | Required: RN, Third Edition, Chapter 18.1-2 |