CS534 Artificial Intelligence

Syllabus— Fall 2006

Prof. Carolina Ruiz

WARNING: Small changes to this syllabus may be made during the semester.

COURSE DESCRIPTION:

This is an introductory graduate AI course.

During the first part of the semester we will cover general knowledge representation techniques and problem solving strategies. Topics will include semantic nets, search, intelligent agents, game playing, constraint satisfaction, rule-based systems, logic-based systems, logic programming, planning, reasoning with uncertainty, and probabilistic reasoning.

During the second part of the semester we will discuss three important application areas in AI: machine learning, natural language processing, and machine vision.

For the catalog description of this course see the WPI Graduate Catalog.

CLASS MEETING:

Tuesdays and Thursdays 4:00 - 5:20 p.m.
SH202

Students are also encouraged to attend the AIRG Seminar Thursdays at 11 am and the KDDRG Seminar Fridays at 2 pm.

INSTRUCTOR:

Prof. Carolina Ruiz

Office: FL 232
Phone Number:

Office Hours: Mondays 1-2 pm, Thursdays 2-3 pm, or by appointment.

TEXTBOOK:

RECOMMENDED BACKGROUND:

Familiarity with data structures and a recursive high-level language.

GRADES:

Exam 1 20%
Exam 2 20%
Project 25%
Homework 35%
Class Participation Extra Points

Your final grade will reflect your own work and achievements during the course. Any type of cheating will be penalized in accordance to the Academic Honesty Policy.

Students are expected to read the material assigned to each class in advance and to participate in class. Class participation will be taken into account when deciding students' final grades.

EXAMS

There will be a total of 2 exams. Each exam will cover the material presented in class since the beginning of the semester. In particular, the final exam is cumulative. The midterm exam is scheduled for October 10 and the final exam is scheduled for December 12.

HOMEWORK AND PROJECS

Homework

There will be several, individual homework assignments during the semester. The homework statements will be posted on the course webpage. Generally homework solutions are due on Tuesdays. Each student should hand-in his/her own individual written homework solutions at the beginning of the class when the homework is due, and should be prepared to present and discuss his/her homework solutions in class immediatly after.

Project

There will be one major course project. This project may consist of several smaller parts. A detailed description of the project will be posted to the course webpage at the appropriate time during the semester. Although you may find similar programs/systems available online or in the references, the design and all code you use and submit for you projects MUST be your own original work.

CLASS MAILING LIST

The mailing list for this class is:

This mailing list reaches the professor and all the students in the class.

CLASS WEB PAGES

The web pages for this class are located at http://www.cs.wpi.edu/~cs534/f06/
Announcements will be posted on the web pages and/or the class mailing list, and so you are urged to check your email and the class web pages frequently.

ADDITIONAL SUGGESTED REFERENCES

General AI

The following additional references complement and/or supplement the material contained in the required textbook. I have listed them in decreasing order of interest according to my own preferences.

  1. T. Dean, J. Allen, Y. Aloimonos. "Artificial Intelligence: Theory and Practice" The Benjamin/Cummings Publishing Company, Inc. 1995.

  2. B. L. Webber, N. J. Nilsson, eds. "Readings in Artificial Intelligence" Tioga Publishing Company, 1981.

  3. Patrick H. Winston. "Artificial Intelligence" 3rd edition Addison Wesley.

  4. S. L. Tanimoto. "The Elements of Artificial Intelligence Using Common Lisp" Computer Science Press 1990.

  5. E. Rich and K. Knight. "Artificial Intelligence" Second edition McGraw Hill 1991.

  6. P. Norvig "Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp" Morgan Kaufmann Publishers, 1992.

  7. M. Ginsberg "Essentials of Artificial Intelligence" Morgan Kaufmann Publishers, 1993.

  8. G. F. Luger and W. A. Stubblefield "Artificial Intelligence Structures and Strategies for Complex Problem Solving" Third edition Addison-Wesley, 1998.

  9. M.R. Genesereth and N. Nilsson, "Logical Foundations of Artificial Intelligence" Morgan Kaufmann, 1987.

Machine Learning

  1. Tom M. Mitchell "Machine Learning" McGraw-Hill, 1997.

  2. P. Langley "Elements of Machine Learning" Morgan Kauffamann Publishers, Inc. 1996.

Lisp/Prolog Textbooks and Manuals

  1. G. L. Steele Jr. "Common Lisp: The language'' 2nd edition Digital Press, 1990. (ISBN 1-55558-041-6)
    This reference is online.

  2. Patrick H. Winston and Berthold K.P. Horn "Lisp" 3rd edition.

  3. L. Sterling, E. Shapiro "The Art of Prolog" MIT Press, 1986.

WARNING:

Small changes to this syllabus may be made during the course of the term.

OTHER AI RESOURCES ONLINE:

WPI Worcester Polytechnic Institute
   

Computer Science Department
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