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Instructor:
Dan Gildea office hours Tu/Th 11-12pm, 3019 Wegmans
TAs:
- Shikhar Srivastava
- Emma Buller ebuller@u
- Dominic Musumeci dmusumec@u
- Zhechao Zhao zzhao46@u
- Siddharth Narsipur snarsipu@u
- Jaclyn Dron jdron@u
- Dylan McKellips dmckelli@u
- Peter Nie jnie7@u
Location: Tu/Th 9:40-10:55am, Wegmans 1400
Prereqs: Data structures and algorithms.
Study sessions:
- Wegmans 2215 Mondays 4:00pm-5:00pm
- Wegmans 3307 Tuesdays 4:00pm-5:00pm
- Wegmans 2215 Wednesdays 11:00am-12:00pm
- Wegmans 2215 Wednesdays 4:00pm-5:00pm
- Wegmans 2215 Thursdays 4:00pm-5:00pm
Projects
Required text: Stuart Russell and Peter Norvig, Artificial Intelligence, A Modern Approach, 4th ed. (2020).
If you want to add the class, complete the first project, and
then email it to gildea@cs along with a note including your
year and major.
Syllabus
| Date | Topic | Reading |
|---|
| 1/18 |
Problem Solving |
3.0-3.3.3 |
| 1/23 |
Search Strategies |
3.3.4-3.6.1 |
| 1/25 |
Adversarial Search |
5.0-5.2.1 |
| 1/30 |
Adversarial Search 2 |
5.3-5.3.2; 5.5-5.6; 5.7 |
| 2/1 |
Local Search |
4.0-4.1 |
| 2/6 |
Local Search 2 |
4.3-4.4; 4.2, 4.5 |
| 2/8 |
Midterm 1 |
|
| 2/13 |
Constraint Satisfaction |
6.0-6.5 |
| 2/15 |
Propositional Logic |
7.0-7.4 |
| 2/20 |
Propositional Theorem Proving |
7.5 |
| 2/22 |
First Order Logic |
8.0-8.3 |
| 2/27 |
First Order Theorem Proving |
9 |
| 2/29 |
no class |
|
| 3/5 |
Midterm 2 |
|
| 3/7 |
midterm solutions |
|
| 3/19 |
Representing Uncertainty |
12.0-12.2; 12.2.3 |
| 3/21 |
Uncertain Inference |
12.3-12.7 |
| 3/26 |
Bayesian Networks |
13.0-13.2.1; 13.3-.3 |
| 3/28 |
no class |
|
| 4/2 |
Approximate Inference in Bayesian Networks |
13.4; 13.5 |
| 4/4 |
Inference in Temporal Models |
14.0-14.2; 14.3 |
| 4/9 |
review / problem solving |
|
| 4/11 |
Learning From Examples, Decision Trees |
19.0-19.3, 19.4.0 |
| 4/16 |
Linear Regression and Linear Classifiers |
19.6, logistic regression |
| 4/18 |
Neural networks |
21.0-21.2, 21.4, 21.5.3, 21.6.1, 24.4.1 |
| 4/23 |
Learning Probabilistic Models |
20.0-20.2.2; 20.2.7 |
| 4/25 |
Learning with Incomplete Data |
20.3.0, 20.3.4 |
| 4/30 |
Review |
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Final Exam: Wednesday, May 8, 4-7 p.m, 1400 Wegmans.
Grading
- Homeworks: 40%
- Midterms: 25%
- Final: 35%
gildea @ cs rochester edu
May 8, 2024
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