CS 511 - Spring 2006 (under construction ...)

Artificial Intelligence II

Course Objective

This course has three objectives. First, to introduce advanced topics. Second, to ensure that students are able to read, and critically evaluate research papers. Third, to ensue that students are able to implement some important algorithms.

If you have questions about any topic or assignment, DO ASK me or even your classmates for help, I am here to make the course undersdood. DO NOT delay your questions. There is no such thing as a stupid question. The only obstacle to learning is laziness.

General Information

• Instructor: Bing Liu
  • Email: Bing Liu
  • Tel: (312) 355 1318
  • Office: SEO 931
• Course Call Number: 17442
• Lecture times:
  • 2:00-2:50pm, Monday, Wednesday, and Friday
• Room: 219 BSB
• Office hours: 2:00pm-3:30pm, Monday and Wed (or by appointment)

Grading

• Final Exam: 40%
  • Time and date: 1:00-3:00pm, 219BSB, Tue, May 2.
• Midterm: 30%
  • Time and date: TBA
• Projects: 20%
• Paper presentation: 10%

Prerequisites

• Knowledge of probability and algorithms
• CS411

Teaching materials

• Reference books
  • Artificial Intellgence: A Modern Approach, Second edition, by Stuart Russell and Peter Norvig, 0-13-790395-2.
  • Expert Systems: Principles and Programming. By Giarratano and Riley, ISBN 0-534-73744-6
  • Machine Learning, by Tom M. Mitchell, McGraw-Hill, ISBN 0-07-042807-7

Main Topics (subject to change)

1. Constraint satisfaction problems Slides
2. Introduction to uncertainty handling Slides
3. Machine learning Slides
4. AI and the Web
   • Supervised and unsupervised wrapper generation Slides
   • Opinion extraction and information synthesis Slides
5. Summary

Project - graded (you will demo your programs to me)

• TBA

Paper presentation - graded

• Schedule has been sent through emails.

Rules and Policies

• Statute of limitations: No grading questions or complaints, no matter how justified, will be listened to one week after the item in question has been returned.
• Cheating: Cheating will not be tolerated. All work you submitted must be entirely your own. Any suspicious similarities between students' work (this includes, exams and program) will be recorded and brought to the attention of the Dean. The MINIMUM penalty for any student found cheating will be to receive a 0 for the item in question, and dropping your final course grade one letter. The MAXIMUM penalty will be expulsion from the University.
• MOSS: Sharing code with your classmates is not acceptable!!! All programs will be screened using the Moss (Measure of Software Similarity.) system.
• Late assignments: Late assignments will not, in general, be accepted. They will never be accepted if the student has not made special arrangements with me at least one day before the assignment is due. If a late assignment is accepted it is subject to a reduction in score as a late penalty.