CSE 473 - Introduction to Artificial Intelligence

University of Washington Department of Computer Science & Engineering

CSE 473 - Introduction to Artificial Intelligence - Spring 2013
Mon, Wed, Fri 1:30-2:20 in ~~BAG 260~~ MUE 153

CSE Home

About Us

Contact Info

Instructor: Luke Zettlemoyer (lsz at cs dot washington dot edu)
Office hours: Tues 11-12 in CSE 658, or by appointment TA: Cynthia Matuszek (cynthia at cs dot washington dot edu)
Office hours: Thur 5:00-6:00pm, CSE 006

TA: Mark Yatskar (my89 at cs dot washington dot edu)
Office hours: Wed 3:00-4:00pm, CSE 006

Schedule [subject to change!]

Week	Dates	Topics & Lecture Notes	Readings
1	April 1, 3, 5	Introduction; Search	R&N, Ch. 1,2 (optional); R&N, Ch. 3.1-3.7
2	April 8, 10, 12	Heuristic Search; Game Playing: Minimax and Expectimax	R&N, Ch. 5.1-5.9 (5.6 is optional)
3	April 15, 17, 19	Games (continued); Markov Decision Processes (MDPs)	R&N, Ch 17.1-17.3; S&B, Ch. 3-4
4	April 22, 24, 26	MDPs (cont.); Reinforcement Learning (RL)	R&N, Ch. 17.4 (also, finish previous reading)
5	April 29, May 1, 3	RL (continued), Uncertainty and Hidden Markov Models (HMMs)	R&N, 13.1-13.5; 15.1-15.3
6	May 6, 8, 10	Constraint Satisfaction Problems, CSP Review	R&N, Ch. 6.1-6.5
7	May 13, 15, 17	HMMs (cont.); Bayesian Networks (BNs)	R&N, Ch. 14.1-14.5
8	May 20, 22, 24	BN Inference; Supervised Learning	R&N, 18.1-2, 18.4, 18.6;
9	May 29, 31	ML (cont.); Intro. Logic	R&N 7-7.5
10	June 3, 5, 7	Logical Inference; First-Order Logic	R&N 8.2-8.3.2, 8.4; 9.1-9.3.2

Course Administration and Policies

Your grade will be 50% programming assignments, 20% written homeworks, 25% take home final exam, and 5% class participation. Questions on the final exam will be of the same general type as on the written assignments, but will include all topics covered in the course.
Assignments will be done individually unless otherwise specified. You may discuss the subject matter with other students in the class, but all final answers must be your own work. You are expected to maintain the utmost level of academic integrity in the course.
Assignments may be handed in up to a week late, at a penalty of 10% of the maximum grade per day.

Textbooks

Stuart Russell & Peter Norvig, Artificial Intelligence: A Modern Approach, Prentice-Hall, Third Edition (2009) [R&N].
Richard Sutton & Andrew Barto, Reinforcement Learning: An Introduction, MIT Press. (limited chapters; freely available online) [S&B]

Programming Projects

This quarter, we will do The Pac-Man Projects. Please complete the versions listed below, as they differ in places from the originals.

Project 0: Python Tutorial (Not Graded)
Project 1: Search in Pac-man (Due Friday April, 19 at 5:00pm in Dropbox)
Project 2: MultiAgent Pac-man (Due Thursday May 2 at 11:45pm in Dropbox)
Project 3: MDPs and RL (Due Thurday May 16, 11:45pm in Dropbox)
Project 4: Ghostbusters (Inference and Filtering) (Due Thurs May 30, 11:45pm)

Written Homeworks

Homework 1: CSPs and Bayes Nets (Due Friday May 24 at 1:30pm in Dropbox or in class.)
Homework 2: BN Inference, ML, and Logic (Due Friday June 7 at 1:30pm in class or in Dropbox.)

Final Exam

Final Exam (Due Friday Jun 14 at 5pm in DropBox or earlier to TA)

Communication

Discussion Forum
Dropbox (submit assignments here)
Grade Book
Comments can be sent to the instructor and TAs using this anonymous feedback form.

Department of Computer Science & Engineering
University of Washington
Box 352350
Seattle, WA 98195-2350
(206) 543-1695 voice, (206) 543-2969 FAX

Instructor: Luke Zettlemoyer (lsz at cs dot washington dot edu) Office hours: Tues 11-12 in CSE 658, or by appointment	TA: Cynthia Matuszek (cynthia at cs dot washington dot edu) Office hours: Thur 5:00-6:00pm, CSE 006
	TA: Mark Yatskar (my89 at cs dot washington dot edu) Office hours: Wed 3:00-4:00pm, CSE 006