## CSE 573: Introduction to Artificial Intelligence

### Autumn 2005

Mon/Wed 1:30-2:50 pm

MOR 225

**Instructor:** Henry Kautz <kautz@cs>

(206) 543-1896

666 Paul J. Allen Center

Office hours: Tuesday 12:30-1:20, Thursday 11:30-12:30, and by appointment

**T****A: **Daniel Lowd <lowd@cs>

218
Paul J. Allen Center

Office hours: Wednesday 3:00-4:00, and by appointment

**Textbook: ***Artificial Intelligence, A Modern Approach: Second Edition*.
Stuart Russell & Peter Norvig. Prentice Hall, 2003. Please note
that you must have the Second Edition.

### Knowledge Post-Conditions

This course will enable you to:

- Represent real-world constraint satisfaction problems in terms of state-space
search, and solve them using a variety of different search algorithms.
- Represent and solve deductive reasoning problems using propositional logic.
- Represent and solve probabilistic reasoning problems using Bayesian networks.
- Use machine learning algorithms, including neural networks and decision
trees, to solve classification problems such as arise in medicine and science.
- Understand how perception, learning, and reasoning interact in an autonomous
AI system.

### Course Work & Grades

There will be weekly problem sets and short programming assignments. There will be a final project that will require a significant amount of thought, programming, and writing. Grades will be 75% based on problem sets and 25% on the final project. There will be no exams.

### Staying in Touch

The course mailing list is: cse573@cs.washington.edu.
Sign up for it here:

https://mailman.cs.washington.edu/mailman/listinfo/cse573

Please use it as a resource to discuss
issues about the course and the assignments with other students. The TA
and instructor will also be reading this list, so it is also appropriate for any
question of a general nature. You may also send email to Daniel or me
directly with either general questions or questions about your own performance
in the course. The course home page is:

http://www.cs.washington.edu/education/courses/573/05au

I encourage people to come to office hours. You do not have to wait
until you have a problem with an assignment.

### Collaboration and Academic Honesty

In this class, you are expected to learn from each other, as well as the text and instructors. You may discuss the problem sets with other students, but you should write up your own solution to hand in. A good way to do this is to go off alone after any group discussions, put away any notes you took in the group, and then reconstruct the answers on your own. If you get help from sources other than other students in the class - such as articles or books other than the text - you should cite them in your writeup.