CSC 529-01: Artificial Intelligence

Spring 2004, Department of Mathematical SciencesUNCG
Web page: http://www.uncg.edu/~nlgreen/csc529-sp04/index.html

Contact Information

 

Instructor: Dr. Nancy Green

Office Hours:Tu/Th3:30-4:30 and by appointment

Email: nlgreen@uncg.edu

Office: 322 Bryan

Phone:  (336) 334-5836

 

Course Description

Time:Tu/Th11:00-12:15


Room: 114 
Bryan

Prerequisites: grade of at least "C" in CSC 330. The course is designed for junior-senior level undergraduate computer science majors or minors, although graduate students that meet the prerequisites may enroll in the course.  Skills developed from previous courses in formal logic and algorithms will be useful.  CSC339 (which covers Prolog) would be helpful but is not required. 

Description:  an overview of the theoretical foundations and main areas in Artificial Intelligence (AI) today.  In addition the course will provide programming experience in AI problems.  Students will be given several short programming assignments using Prolog and a larger project using Prolog or possibly other AI tools.  Students will be expected to explain the AI methods and algorithms used in their project and give a demonstration of the project.  In addition, graduate students are expected to write a report on an application of AI based on sources in the research literature and to make a presentation to the class on their report.  Also, graduate students' examinations may contain different questions. 

Required Textbook:Computational

 Intelligence: A Logical Approach

, by PooleMackworth, & Goebel. Oxford U. Press, 1998.[Comes with CISpace applets and lecture overheads.] 

Supplementary Textbook (optional): Prolog Programming for Artificial Intelligence, by Ivan Bratko, 3rd ed. Addison Wesley, 2001. [Comes with prolog code.

  (more direct link here)] 

Student Learning Outcomes: By the end of the course, students (1) should be able to demonstrate understanding of the basic concepts, methods, and algorithms of Artificial Intelligence covered in the course, and (2) should be able to implement programs (using Prolog and possibly other AI tools) implementing AI methods and algorithms.  In addition, graduate students should be able to locate, evaluate, and communicate information presented in the related technical literature. 

Topics (not everything on this list can be covered in one semester):

·Logical Foundations of Representation and Reasoning 

·Logic Programming Methods 

·Search 

·Planning 

·Reasoning under uncertainty 

·Situated robots 

·AI applications (ex. natural language processing, medical diagnosis, entertainment, learning systems) 

Course Policies

Missed Tests: Tests missed due to severe illness or other emergency situations may be made up if (1) the absence is excused by the instructor before the exam is graded, (2) appropriate written documentation of the illness or situation (specified by the instructor) is provided when the exam is made up, and (3) the exam (or alternate work specified by the instructor) is made up by the date specified by the instructor.  Note that it is the student's responsibility to satisfy these conditions.  An exam that is not made up will receive a grade of 0. 

Attendance: Attendance is expected.  If you miss more than 5 classes (not counting days on which tests are given or days when class was officially cancelled due to winter storm, etc.) you may be dropped from the course.  (If you are dropped after the last day to withdraw without academic penalty you may receive WF.) 

Grading: The final course grade will be assigned based upon the following factors:

 

 

25

25

25

25

15

15

5

5

5

5

5

5

5

15

15

5

100

Samples of student work (tests and assignments) may be shown to reviewers for department accreditation. 

Calendar (last updated: Jan. 30, 2004)


 

 

 


Jan. 21 is last day to drop course with refund

 

 

 

 

 


(Spring Break)

 

 


Mar. 17 is last day to drop course without academic penalty


Knowledge Engineering 
(Expert Systems part II)

Bratko p. 360-363

 

 

 

 

ch. 8 (through p. 304), Bratko p. 414-420

SR  presents 4/15

 


HW5 due Apr 27 (Demos est. 15 min per person, 5 per class)


no class 

 

 


final exam day

See handout on what will be covered


Course Resources

Prolog

·my UNCG Prolog notes

·http://www.amzi.com/ (tutorial

·http://www.swi-prolog.org/

Other AI Languages and Software

·Bayesian Belief Networks (index to many products)

·CLIPS

·Lisp

·Ruth (talking heads)

·Soar (cognitive architecture)

·Soar in Computer Games (QuakeBot)

Artificial Intelligence Publications (big bibliography)

·ACL Digital Archives (Computational Linguistics) (on-line

·AI Magazine (back issues on-line

·Intelligence (SIGART bulletin) (available on-line through ACM Digital Library) 

·Journal of AI Research (on-line)

General AI Conferences inNorth America

·AAAI-2004 

·AAAI Spring 2004 and Fall 2005 Symposia Series

· FLAIRS-2004 

AI Applications Resources (other info on applications)

·AI in Education: Int. AI in Ed. Soc., other info

·AI in Entertainment: CSC589-01 (Spring 2002), other info

·AI in Medicine: American Medical Informatics Assoc., other info

·Machine Learning

·Natural/Human Language Technology: ACL,other info

  

 

Send comments and requests about this web site to nlgreen@uncg.edu