PSU CS441/541 Artificial Intelligence
Fall 2000
Course Syllabus

When: 1800-2130 (6:00-9:30PM) Mondays
Where: PCAT 28
Who: Bart Massey <bart@cs.pdx.edu>
Office Hours:Thursdays 10:00-11:00, or by e-mail appointment
CRN: 10664(441), 10681(541)
Assistant:Qiong Chen, <qchen@cs.pdx.edu>

What: The catalog says

Artificial Intelligence (4/3)

Introduction to the basic concepts and techniques of artificial intelligence. Knowledge representation, problem solving, and AI search techniques. Program will be written in one of the AI languages. Prerequisites: CS 202, 252.

This course explores the ideas behind Artificial Intelligence, from philosophical underpinnings to the grungy details of coding.

Prerequisites:

E-mail

There are two special e-mail addresses associated with the course. Mail to <cs541@cs.pdx.edu> will contact myself and your teaching assistant personally: use this for homework submissions, class questions, etc. <cs541-discuss@cs.pdx.edu> is the course mailing list (using majordomo). Subscribe to this by sending an e-mail message to majordomo@cs.pdx.edu with subscribe cs541-discuss in the body, and use it for class discussions and the like.

Readings

Required Text:

Matt Ginsberg
Essentials of Artificial Intelligence
Morgan Kaufman 1993
ISBN 1-55860-221-6

Other Readings

[AdvS]
Dr. Richard Korf
Heuristic Search, chapter 7
Unpublished MS, 1999
(class handout)
[CSP]
Dr. Edward Tsang
Principles Of Constraint Satisfaction, chapter 1
Out-of-print MS, 1993
(class handout)

Links

Coursework

The coursework will consist of a series of projects, largely implementing various ideas from the text, culminating in a final larger project. (Those experimenting with departmental computers must follow the ``safety guidelines''.) There will be midterm and final examinations.

Deliverable %
Homework 40%
Project 30%
Midterm Exam 10%
Final Exam 20%

Academic Honesty

If I catch you plagiarizing any material, I will do what I can to end your academic career. Plagiarism is using anyone else's works, writings, or ideas without explicitly giving them credit. If you get code, ideas, or text from a fellow student, put their name on it so that we both know what happened.

Course Schedule

Date Topics Readings HW
9/25 Introduction To AI Ginsberg ch. 1-2  
10/2 AI Problem Representation Ginsberg ch. 6-7 HW 1: Logical Representation
10/9 Single Agent Search Ginsberg ch. 3-4 HW 2: SAT Search
10/16 First-Order Databases Ginsberg ch. 8-9  
10/23 Midterm Examination
Adversary Search
Ginsberg ch. 5, [AdvS] HW 3: Tic-Tac-Toe Board Evaluation
10/30 Advanced KR: Three Topics Ginsberg ch. 11-12, [CSP]  
11/6 Planning Ginsberg ch. 14 Project: Lines Of Action
11/13 Machine Learning Ginsberg ch. 15  
11/20 Natural Language Ginsberg ch. 17  
11/27 Review    
12/4 Final Examination    


Last Modified: 2000/12/4