CS486/686 - Schedule

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

[RN2] 2nd edition of Artificialtop Intelligence: A Modern Approach by Russell and Norvig
[RN3] 3rd edition of Artificial Intelligence: A Modern Approach by Russell and Norvig
[GBC] Ian Goodfellow, Yoshua Bengio and Aaron Courville, Deep Learning (2016) freely available online

Lecture
 Date
 Topic
 Reading (textbook)
1
 May 1
 Introduction (Lecture slides) [RN2] Chapt. 1 and 2
[RN3] Chapt. 1 and 2
2
 May 3
 Uninformed Search (Lecture slides) [RN2] Sect. 3.1-3.5
[RN3] Sect. 3.1-3.4
3
 May 8
 Informed Search (Lecture slides) [RN2] Sect. 4.1-4.2 (except RBFS)
[RN3] Sect. 3.5-3.6 (except RBFS)
4
 May 10
 Constraint Satisfaction Problems (Lecture slides) [RN2] Sect. 5.1-5.2
[RN3] Sect. 6.1-6.3
5
 May 15
 Local Search (Lecture slides) [RN2] Sect. 4.3
[RN3] Sect. 4.1
6
 May 17
 Uncertainty (Lecture slides) [RN2] Sect. 13.1-13.6
[RN3] Sect. 13.1-13.5

May 19
 Assignment 1 due (11:59 pm)
7
 May 23
 Bayesian Networks (Lecture slides) [RN2] Sect. 14.1-14.2
[RN3] Sect. 14.1-14.2
8
 May 24
 Bayesian Networks (Lecture slides (Slide 24 revised June 12)) [RN2] Sect. 14.4 (except clustering algorithms)
[RN3] Sect. 14.4 (except clustering algorithms)
9
 May 29
 Decision Theory (Lecture slides) [RN2] Sect. 16.1-16.3
[RN3] Sect. 16.1-16.3
10
 May 31
 Decision Networks (Lecture slides) [RN2] Sect. 16.5-16.6
[RN3] Sect. 16.5-16.6

Jun 2
 Assignment 2 due (11:59 pm)
11
 Jun 5
 Probabilistic reasoning over time (Lecture slides) [RN2] Sect. 15.1-15.3, 15.5 (except approximate inference)
[RN3] Sect. 15.1-15.3, 15.5 (except approximate inference)
12
 Jun 7
 Markov Decision Processes (Lecture slides (Slide 11 revised June 12)) [RN2] Sect. 17.1-17.2, 17.4-17.5
[RN3] Sect. 17.1-17.2, 17.4
13
 Jun 12
 Decision tree learning (Lecture slides (Slide 28 revised July 27)) [RN2] Sect. 18.1-18.4
[RN3] Sect. 18.1-18.4
14
 Jun 14
 Review and QA session to prepare for midterm

Jun 16
 Midterm 6:30 - 8:00 pm
  • MC-4021: Students with last name starting with A-K
  • MC-2017: Students with last name starting with L-S
  • M3-1006: Students with last name starting with T-Z

15
 Jun 19
 No new material
16
 Jun 21
 Statistical Learning (Lecture slides) [RN2] Sect. 20.1-20.2 (up to p. 718)
[RN3] Sect. 20.1-20.2 (up to p. 809)

Jun 23
 Project proposal due (11:59 pm)
17
 Jun 26
 Neural networks (Lecture slides (revised July 28))
 [RN2] Sect. 20.5
[RN3] Sect. 18.7
18
 Jun 28
 Deep neural networks (Lecture slides)
 [GBC] Chap. 6, 7, 8

Jun 30
 Assignment 3 due (11:59 pm)
19
 Jul 5
 Reinforcement Learning (Lecture slides)
 [RN2] Sect. 21.1-21.3
[RN3] Sect. 21.1-21.3
20
 Jul 10
 Deep reinforcement learning (Lecture slides (revised July 26))
 [Human-Level Control through Deep Reinforcement Learning, Nature 2015]
21
 Jul 12
 Deep reinforcement learning (Lecture slides)
 [Mastering the Game of Go with Deep Neural Networks and Tree Search, Nature 2016]
22
 Jul 17
 Multi-armed Bandits (Lecture slides, video)
 [Sutton and Barto, Reinforcement Learning, 2nd edition, Chapter 2]
Supplementary lecture slides, supplementary video
23
 Jul 19
 Sum-product networks (Lecture slides, video)
 Supplementary lecture slides, supplementary video

Jul 21
 Assignment 4 due (11:59 pm)
24
 Jul 24
 Course wrap up (Lecture slides)

Jul 30
 Project report due (11:59 pm)