Lectures for Artificial Intelligence I (COMP-424)

Winter 2014


Lecture notes will be linked to this web page, in PDF format. The reader for PDF files is available free from Adobe for UNIX, Apple Macintosh, and Windows.

Schedule

Lec.
Date
Topic
Readings
Slides
To-do (TENTATIVE DATES! Check frequently.)
1
Jan. 7
Introduction RN, Chapter 1 & 2
2
Jan. 9
Search (uninformed) RN, Chapter 3
3
Jan. 14
Search (informed) RN, Chapter 3
4
Jan. 16
Search (optimization) RN, Section 4.1
5
Jan. 21
Search (under uncertainty) RN, Sec. 4.2-4.5
6
Jan. 23
Constraint satisfaction RN, Chapter 6
7
Jan. 28
Game playing (Minimax) RN, Chapter 5
8
Jan. 30
Game playing (Monte-Carlo search trees) RN, Chapter 5
9
Feb. 4
Logical reasoning (propositional logic) RN, Chapter 7
10
Feb. 6
Logical reasoning (first-order logic) RN, Chapters 8, 9
11
Feb. 11
Sequential logical reasoning (classical planning) RN, Chapter 10
12
Feb. 13
Probabilistic reasoning (basics) RN, Chapter 13
13
Feb. 18
Midterm Exam (DATE NOT CONFIRMED)

14
Feb. 20
Probabilistic reasoning (Bayesian networks)
RN, Sec. 14.1, 14.2, 14.4
15
Feb. 25
Probabilistic reasoning (Bayesian networks cont'd) RN, Sec. 14.1, 14.2, 14.4
16
Feb. 27
Learning probabilistic models with complete data RN, Sec. 20.1-20.2 (up to p.719)
Mar. 4
Study week.
Mar. 6
Study week.
17
Mar. 11
Learning probabilistic models with missing data RN, Sec. 20.3
18
Mar. 13
Reasoning with temporal probabilistic models (HMMs) RN, Sec. 15.1-15.3
19
Mar. 18
Learning temporal probabilistic models (Baum-Welch) RN, Sec. 20.3
20
Mar. 20
Reasoning with utilities RN, Chapter 16
21
Mar. 25
Learning utilities from exploration (Bandits) RN, Sec. 21.3
22
Mar. 27
Sequential reasoning (Markov Decision Processes) RN, Sec. 17.1 - 17.3
23
Apr. 1
Sequential reasoning (Markov Decision Processes, cont'd)
24
Apr. 3
Learning sequential decisions (Reinforcement Learning) RN, Chapter 21
25
Apr. 8
Reasoning under uncertainty (POMDPs) and/or with multiple agents RN, Sec. 17.4-5
26
Apr.10
AI: Present and Future. RN, Chapters 26 and 27