Artificial Intelligence (W4701)

General Information for Fall, 1999

Professor: Eric V. Siegel ( email: evs at cs dot columbia dot edu ). Office: 703 CEPSR, 939-7112

Eric Siegel now provides predictive analytics services at Prediction Impact, Inc., where predictive modeling and data mining are applied to gain customer intelligence.


Despite its relative youth, Artificial Intelligence is a vast field, since it is all-inclusive of systems designed to be intelligent or to approach a task that is considered to require intelligence. Therefore, the list of main topics below is only the very top of a deep hierarchy. Although we can only cover the upper portions of this hierarchy this semester, we will delve into greater detail in certain select areas.

Main topics:

Other topics incorporated, time permitting:

There will not be time to cover all applications of AI; most of vision, speech understanding and robotics are omitted.

On-line homework projects

  1. Search Methods: Quest for Palindromes
  2. Knowledge representation: what and when
  3. Logic: rules, inference, planning and uncertainty
  4. Machine induction: concept learning and decision trees
Additionally, each project will include extensive written exercises. Knowledge of Java may be desirable for some of the project, but in general we allow you to do the homework in the language of your choice. Note that this list is subject to change.

Prerequisite: W3139 (Data Structures and Algorithms). Please do not forget that W3203 (Discrete Math) is a co-requisite for W3139 and is thus also a prerequisite for this class.

Text: Artificial Intelligence: A Modern Approach, by Russel and Norvig, Prentice Hall, 1995. ISBN # 0-13-103805-2. Readings will also included papers handed out in class.

Grading : 60% homework, 15% midterm, 25% final exam. To receive a passing grade, you must complete satisfactory work in every area. In other words, you must receive passing grades for your homework (cumulatively), and a passing grade on your midterm and final.

Late homework: Late assignments will not be accepted without the TA's prior permission. Extensions are available only in the case of dire emergencies. You should hand in what you have on time, since partial credit will be considered for all incomplete work.

Computer account: Each student is required to obtain an extended Columbia student machine account. This account is included in the regular fees for Columbia University undergraduates. For all other students (graduate school, Barnard, Teacher's College, etc.), there is a $45 fee.

Course web page A web page will be set up and communication with the class pertaining to assignments, grades, changes in requirements etc. will be via this medium. The class web page is This page will have further links to pages with handouts, demos, etc. Students are required to log in and check this web site at least every few days to make sure they are up to date with any information pertaining to the course. The Web site is the primary means of getting information to you outside of class.

Collaboration: Discussion of material covered in class is strongly encouraged. Some assignments may be designated as collaborative. Otherwise, the work you submit must be your own work.

Homework grading: In case of grading difficulties, the order of appeals will be the TA who graded your submission, the head TA (if not the same TA), and then the instructor. All rulings by the instructor are final.

Open Door Policy: We would like the course to run smoothly and enjoyably. Feel free to let us know what you find good and interesting about the course. Let us know sooner about the reverse. See us, leave us a note, or send us an e-mail.

F99 Announcements (reverse chronological):

email: evs at cs dot columbia dot edu