CSE 571: Artificial Intelligence
Class: COOR 174, T/Th, 4:30--5:45PM
Office Hours: BYENG 594, T/Th, 3:15--4:15PM
Office Hours (TA: Mehrdad): BYENG 221, M 3-5PM, F 2-4PM
| Course home | Syllabus | Schedule | Student Projects |
Subject to change. Check back frequently for updates.
Last updated: Nov 29, 2018
| Date | Topics | Lecture Notes |
Reading/Project Assignments | Deadlines | Important Dates |
| Th. 08/16 | Course introduction. | Lecture Slides | Recommended: R&N, Third Edition, Chapter 1 | ||
| Tue. 08/21 | Rational agent. | Lecture Slides | Required: R&N, Third Edition, Chapter 2 |
Project assignnment #0 (warmup; no credit): Python tutorial. |
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| Th. 08/23 | Uninformed search. | Lecture Slides | Required: R&N, Third Edition, Chapter 3.1--3.4 | ||
| Tue. 08/28 | Uninformed search (cont.) | Lecture Slides | Required: R&N, Third Edition, Chapter 3.1--3.4 | ||
| Th. 08/30 | Informed search. | Lecture Slides | Required: R&N, Third Edition, Chapter 3.5--3.6 | ||
| Tue. 09/04 | Adversarial search. | Lecture Slides | Required: R&N, Third Edition, Chapter 5 | ||
| Th. 09/06 | Adversarial search (cont.) | Lecture Slides | Required: R&N, Third Edition, Chapter 5 | ||
| Tue. 09/11 | Games and utilities | Lecture Slides | Required: R&N, Third Edition, Chapter 5 | ||
| Th. 09/13 | Markov Decision Process | Lecture Slides | Required: R&N, Third Edition, Chapter 17.1-2 | ||
| Tue. 09/18 | Markov Decision Process (cont.) | Lecture Slides | Required: RN, Third Edition, Chapter 17.1-2 | ||
| Th. 09/20 | Markov Decision Process (II) | Lecture Slides | Required: RN, Third Edition, Chapter 17.3 | ||
| Tu. 09/25 | Markov Decision Process (III) | Lecture Slides | Required: RN, Third Edition, Chapter 17.3 | ||
| Th. 09/27 | Reinforcement Learning | Lecture Slides | Required: RN, Third Edition, Chapter 21.1-3 | ||
| Tu. 10/02 | Reinforcement Learning II | Lecture Slides | Required: RN, Third Edition, Chapter 21.1-3 | ||
| Th. 10/04 | Reinforcement Learning II | Lecture Slides | Required: RN, Third Edition, Chapter 21.4-5 | ||
| Tue. 10/09 | Fall break | ||||
| Th. 10/11 | Reinforcement Learning II (cont) | Lecture Slides | Required: RN, Third Edition, Chapter 21.4-5 | ||
| Tu. 10/16 | Probability basics | Lecture Slides | Required: RN, Third Edition, Chapter 13 | ||
| Th. 10/18 | Markov Model and HMM | Lecture Slides | Required: RN, Third Edition, Chapter 15.1-3 | ||
| Tue. 10/23 | Markov Model Applications | Lecture Slides | Required: RN, Third Edition, Chapter 15.1-3 | ||
| Th. 10/25 | Bayesian network | Lecture Slides | Required: RN, Third Edition, Chapter 14.1-2 | ||
| Tue. 10/30 | TensorFlow Tutorial | ||||
| Th. 11/01 | Bayesian network (cont.) | Lecture Slides | Required: RN, Third Edition, Chapter 14.1-2 | ||
| Tue. 11/06 | Bayesian network (cont.) | Lecture Slides | Required: RN, Third Edition, Chapter 14.1-2 | ||
| Th. 11/08 | Bayesian network (cont.) | Lecture Slides | Required: RN, Third Edition, Chapter 14.4-5 | ||
| Tue. 11/13 | Machine learning | Lecture Slides | Required: RN, Third Edition, Chapter 18.1-2 | ||
| Th. 11/15 | Perceptron | Lecture Slides | |||
| Tue. 11/20 | Learning in Neural Networks | Lecture Slides | Recommended: Deep Learning 6.5 | ||
| Th. 11/22 | Thanksgiving holiday. Happy thanksgiving! | ||||
| Tue. 11/27 | Learning in Neural Networks (cont.) | Lecture Slides | Recommended: Deep Learning 6.5 | ||
| Th. 11/29 | CNN | Lecture Slides | Recommended: Deep Learning 9.1-9.3 |