CMSC 25000 - Winter 2009
Introduction to Artificial Intelligence

We will have a midterm Friday, March 6

General information

Instructor: Pedro F. Felzenszwalb
email: pff (at) cs.uchicago.edu
office hours: after class or by appointment

TA: Morgan Sonderegger
email: morgan (at) cs.uchicago.edu
office hours: Tu/Th 3:00-4:00 in Ryerson 257

Lecture: MWF 1:30-2:20 in Ryerson 251
Textbook: Artificial Intelligence: A Modern Approach by Russell and Norvig

This course will cover some of the basic principles in artificial intelligence including search, constraint satisfaction, probabilistic reasoning and learning. We will consider applications in pattern recognition, language and vision.

Homework

Homework 1, due Friday January 16.
You should do this homework on your own. The assigment is available here

Homework 2, due Wednesday January 28.
You can discuss this homework with other students but you should do the programming on your own. The assigment is available here

Homework 3, due Wednesday February 11.
You can discuss this homework with other students but you should do the programming on your own. The assigment is available here
Datafiles for problem 3: data.zip

Homework 4, due Wednesday February 25.
You can discuss this homework with other students but you should write up the solutions on your own. The assigment is available here

Homework 5, due Wednesday March 4.
You can discuss this homework with other students but you should write up the solutions on your own. The assigment is available here

Approximate Syllabus

1. Introduction to AI
2. Search, BFS (chapter 3)
3. Search, DFS and variants (chapter 3)
4. Heuristic functions, A* (chapter 4)
5. Constraint satisfaction problems, Line labeling
6. Solving CSP (chapter 5)
7. Constraint propagation, arc-consistency (chapter 5)
8. Supervised Learning (chaper 18)
9. Learning decision trees
10. Linear threshold functions
11. Perceptron algorithm
12. Large margin separator
13. PAC Learning
14. VC dimension
15. Bayesian networks (Chapter 14)
16. Hidden Markov Models
17. Recovering corrupted sentences
18. Computer vision - camera geometry
19. Stereo
20. Optical flow