Saint Louis University |
Computer Science 362
|
Dept. of Math & Computer Science |
Also note: For each lecture, we denote both a topic as well as the associated reading in the textbook. The live link on the 'topic' leads to a page of my personal notes for that lecture. Those personal notes are not nearly as complete or polished as the associated readings from the text. In truth, they exist mostly to provide a brief outline of the day's lecture. Students are expected to read the associated sections of the text. In cases where my notes include material which is not explicitly in the text, I will add the word "notes" to the explicit reading list.
| Week | Day | Topic | Reading |
|---|---|---|---|
| Aug 27, Aug 29 | Tues |
Course administration,
Introduction to AI |
syllabus
Ch. 1 |
| Thur | Intro. to Propositional Logic |
Ch. 2.1-2.3
(my notes) |
|
| Sep 3, Sep 5 | Tues | CNF, Resolution |
Ch. 2.4
(my notes) |
| Thur | Horn Clauses, Backward Chaining |
Ch. 2.5
(my notes) |
|
| Sep 10, Sep 12 | Tues | First-Order Predicate Logic |
Ch. 3
(my notes) |
| Thur |
Limits of Computation
Introduction to Prolog |
Ch. 4
Ch. 5 (my notes) |
|
| Sep 17, Sep 19 | Tues |
more Prolog
(arithmetic, lists) |
(my notes) |
| Thur |
more Prolog
(output, cuts, examples) |
(my notes) | |
| Sep 24, Sep 26 | Tues | In-class work on asgn03 | asgn03 |
| Thur | Search Algorithms: Uniformed Search |
Ch. 6
(my notes) |
|
| Oct 1, Oct 3 | Tues | Search Algorithms: Heuristic Search |
Ch. 6
(my notes) |
| Thur |
Two-Player Games
Minimax Search Alpha-Beta Pruning |
Ch. 6.4, 6.5
(my demos) (another demo) |
|
| Oct 8, Oct 10 | Tues |
Alpha-beta with heuristics
Move ordering Other practical considerations |
|
| Thur | Discussion of Pente code and asgn04 | asgn04 | |
| Oct 15, Oct 17 | Tues | Exam Review | |
| Thur |
Midterm Exam
(includes material through Oct 3 - info ) |
||
| Oct 22, Oct 24 | Tues | No Class: Fall Break | |
| Thur | Discrete Probability |
Ch. 7.1, 7.2
(my notes) |
|
| Oct 29, Oct 31 | Tues | Bayesian Networks |
Ch. 7.4
(my notes) |
| Thur |
Intro. to Machine Learning
Superverised Learning Perceptron Algorithm |
(my notes) | |
| Nov 5, Nov 7 | Tues | Naive Bayesian classification | |
| Thur |
k-Nearest Neighbor classification,
Decision Tree classification |
||
| Nov 12, Nov 14 | Tues | Introduction to asgn06 | |
| Thur | Continued work on asgn06 | ||
| Nov 19, Nov 21 | Tues | Introduction to Artificial Neural Networks | Ch. 8 |
| Thur | Hopfield Networks | (notes and software) | |
| Nov 26, Nov 28 | Tues | ||
| Thur | No Class: Thanksgiving | ||
| Dec 3, Dec 5 | Tues | ||
| Thur | |||
| Dec 17 | Tues | Final Exam (2:00-3:50) | |