GEORGE MASON UNIVERSITY

SPRING-2008

CS580 – Introduction to Artificial Intelligence (3)

Professor Harry Wechsler

(SITE II - Rm. 461) wechsler@cs.gmu.edu

Class Information

001 113591 M (“Monday”)  4:30 p.m. – 7:10 p.m.  ST120

Office Hours

Monday   3:15 – 4:00 PM or by appointment (SITE II - Rm. 461)

Textbook

S. Russell and P. Norvig   Artificial Intelligence: A Modern Approach,  Prentice Hall, Second edition, ISBN: 0-13-790395-2, 2003. 

Web site: http://aima.cs.berkeley.edu/

http://aima.eecs.berkeley.edu/slides-pdf/

Reference - Johnson Center Library – Reserve Desk

Artificial Intelligence (4th Edition) by George Luger, Addison Wesley, 2002

Recommended Readings 

Graham P., ANSI Common Lisp, Prentice Hall, ISBN: 0133708756, available on line.

http://aima.cs.berkeley.edu/ai.html#prolog

Course Description ~ Syllabus

Artificial Intelligence (AI) is about the Science, Engineering, and Technology involved with the theory and practice of developing systems that exhibit the characteristics associated with intelligence in human behavior.  The course presents basic AI principles and (“computer”) methods that address search and problem solving [with applications to game playing, and constraint satisfaction problems (CSP)],  knowledge representation and reasoning [including resolution with refutation, reasoning with uncertainty and Bayesian (belief) Networks (BN), (symbolic, connectionist, and evolutionary) learning [including performance evaluation and error analysis], and communication [including natural language processing and perception]. LISP, PROLOG, and MATLAB are the AI programming languages of choice used to implement the methods learned during the course. The approach used throughout the course is to address specific intelligence tasks [relate to real-life problems], and motivate and describe their (algorithmic) solutions.

 

Grading

Homework ŕ 20 %

Midterm ŕ Thursday, March 17 ŕ 25 %

Computer Project [using LISP, PROLOG, or MATLAB] ŕ 25 %

[spring break ~ week of March 10]

Final ŕ Monday, May 12 ŕ 30 %

   

    Follow – up

 

      CS 688 Pattern Recognition and Neural Networks

 

     CS 750 Data Mining

 

      CS 775 / IT 844 – Advanced Pattern Recognition

 

     CS 778

 

      Graduate Certificate in Biometrics

     http://cs.gmu.edu/programs/masters/MSCS-brochure.html

 

     Doctoral Dissertation