CSE440: Introduction to Artificial Intelligence

Fall 2006

Time:  12:40-2:00pm, Monday and Wednesday
Location: 1225 Engineering Building 
Professor: Joyce Chai, 2138 Engineering Building, 517-432-9239, jchai AT cse DOT msu DOT edu
Office Hours: Monday:  2:00-4:00pm, or by appointment
Textbook: Artificial Intelligence: A Modern Approach (2nd Edition)  by Stuart Russell and Peter Norvig, Prentice Hall, 2003.
Teaching Assistant   Feng Kang, kangfeng AT cse DOT msu DOT edu
Office Location EB3353
Office Hours Tuesday 2:00-4:00pm, Wednesday 2:00-4:00pm

Course Description:

This is an introduction course to artificial intelligence covering fundamental topics in problem solving, heuristic search, knowledge representation, inference, planning, probabilistic reasoning, learning, and natural-language processing. 

Course Grades:

Attendance, seminar, class participation 3%
Seven  Homework Assignments 42%
Midterm 1 15%
Midterm 2 15%
Final Exam 25%

Homework and Examinations:

The work in this course consists of seven homework assignments, two midterm exams, and one final exam. The homework assignments usually include a written part and a programming part. The written assignments must be turned in at the beginning of lecture on the day it is due. The programming assignments are due before the midnight of the due date (through handin facility). No late homework will be accepted. Exams will be closed book. There will be NO make-up exams except under extremely exceptional circumstances which must be documented and discussed with the professor ahead of time. The final exam will be comprehensive. 

Due date
Homework 1: September 11
Homework 2: written and programming part: September 25
Homework 3: written part: October 9; project: October 11
Homework 4: written part: October 23; programming part: October 25
Homework 5: November 6
Homework 6: written part and programming part:  November 20
Homework 7: written part and optional programming part: December 4 
Midterm 1 October 4 (Wednesday)
Midterm 2 November 8 (Wednesday)
Final Exam: Tuesday, December 12, 12:45-2:45 p.m.

Tentative Schedule of Topics

Topic Reading
Aug. 28, 30 Introduction and Intelligent Agent Chapters 1; 2
Sept. 6 Search Chapter 3
Sept. 11, 13 More intelligent search Chapter 4.1-4.3
Sept. 18, 20 CPS, Games Chapter 5.1-2; 5.4; 6.1-3
Sept. 25, 27 Propositional Logic, First Order Logic Chapter 7.1-5; 
Oct. 2, 4 Midterm 1
Oct. 9, 11 Inference in FOL Chapter 8. 1-3;  9. 
Oct. 16, 18 Knowledge representation Chapter 10.1-3;  
Oct. 23, 25 Planning  Chapter 11. 1-3
Oct. 30, Nov. 1 Uncertainties, Bayes rules and Naive Bayesian Classifier Chapter 13
Nov.6, 8 Midterm 2
Nov. 13, 15 Bayesian Networks and its applications Chapter 14.1-2 & 4
Nov. 20  Decision Trees  Chapter 18. 1-3
Nov. 27, 29 Concept learning, Version space Chapter 19. 1. 
Dec. 4, 6 Machine learning and its applications, final review

Class notes and homework assignments are here  for your reference. 

Academic Honesty:

Your grade should reflect your own work. Copying or paraphrasing someone's work (code included), or permitting your own work to be copied or paraphrased, even if only in part, is not allowed, and will result in an automatic grade of 0 for the entire assignment in which the copying or paraphrasing was done. Please talk to the instructor if you have trouble completing an assignment.

Alternative Testing:

Alternative testing is available to those with a documented disability affecting performance on tests. Students with documented disabilities requiring some form of accommodation receive a Verified Individualized Services and Accommodations (VISA) document which displays verified testing accommodations when appropriate. Please visit Alternative Testing Guidelines if applied. 

Notes: The instructor reserves the right to modify course policies and the course calendar according to the progress and needs of the class.