Announcements

Course Information

Lecture

1 unit (3 or 4 hours), Tue/Thr 2:00PM - 3:15PM, 1404 Siebel Center

Professor: Eyal Amir

TA: Li-Lun Wang

TA: Mark Richards

Course Description

Major topics in and directions of research in artificial intelligence: AI languages (LISP and PROLOG), basic problem solving techniques, knowledge representation and computer inference, machine learning, natural language understanding, computer vision, robotics, and societal impacts. Same as ECE 448. 3 undergraduate hours. 3 or 4 graduate hours. Prerequisite: CS 225 or ECE 390.

Prerequisites

Syllabus

Machinery: Tasks and Coursework

The course will consist of lectures by the professor, one midterm, one final exam, and homework assignments. Students taking four hours of credit will have a final project. Due dates and recommended course materials are indicated in the syllabus.

Late Policy

Assignments (including homeworks and projects) must be handed in during the class on the date indicated in the syllabus. Recognizing that students may face unusual circumstances and require some flexibility in the course of the quarter, each student will have a total of seven free late (calendar) days to use as s/he sees fit. Once these late days are exhausted, any paper or proposal turned in late will be penalized at the rate of 20% per late day (or fraction thereof). Under no circumstances will an assignment be accepted more than a week after its due date. Late days are from noon to noon.

Late assignments should be turned in at the turn-in box inside the course secretary, Ronda's office (3316 Siebel). You must write the time and date of submission on the assignment. Alternatively, you can fax it to the course secretary (Fax: (217) 265-6591)

Collaboration Policy

High-level collaboration for understanding the material is encouraged. However, you have to work out your solutions on you own. Low-level collaboration for detailed solution is not allowed.

Cheating

Copying assignments or projects from external sources or students, and all other kinds of cheating is strictly prohibited. Students are encouraged to discuss their approach to solving assignment problems with other students or the Instructor/TA's but each individual must develop and present his solution independently. At the first instance of cheating, a grade of 0 will be assigned for that component. On the second instance, the course grade will automatically become 'F'.

Final grade

The final grade for 3 credit points will be calculated using the following formula:
Midterm(25%)+Final(35%)+HW(40%)

The final grade for 4 credit points will be calculated using the following formula:
Midterm(25%)+Final(25%)+HW(25%)+Proj(25%)

Please see Professor Amir after the first class for the project if you are taking 4 hours of credit.

Up to 3% extra credit may be awarded for class participation.

Communication

We strongly encourage students to come to office hours or post on the newsgroup (news.cs.uiuc.edu/class.cs440) instead of emailing questions, except for questions that are only individually relevant. Occasionally the TA may need to broadcast a message to the entire class. We will do so over the newsgroup.

Please do not email us with grading questions. If you want an explanation for why we took points off, you can talk to us after class or during office hours. If you want a regrade, please write an explanation and hand the assignment and the explanation to the TA during office hours or after class.

Reading and Reference

The primary reading materials will be book chapters and papers as described in the syllabus. The textbook is
Stuart Russell and Peter Norvig, Artificial Intelligence, a Modern Approach, Prentice Hall, 2nd ed., 2003.

Other books/papers that can be used for further reading on particular topics will be mentioned during the relevant lecture.

Useful Links and Resources