CSC529 - Artificial Intelligence - Spring 2008

Department of Computer Science, University of North Carolina at Greensboro

Instructor: Dr. Nancy Green, phone: (336) 256-1133
Class Meetings: Tu/Th 11:00-12:15 pm, Petty 223
Instructor's Office Hours: 330-430 Th and by appointment
Course web page: lookup on http://www.uncg.edu/~nlgreen
Course Description Course Calendar Grading Policies Resources Project

Course Description

 Prerequisites: Grade of at least C in CSC330 (or equivalent if transfer student). 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 discrete mathematics will be useful.  CSC339 (which covers Prolog) would be helpful but is not required. 

Brief 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 used in their project and give a demonstration of the project.  In addition, graduate students are expected to read a research paper on an application of AI and to make a presentation to the class on the paper.  Also, graduate students' examinations may contain different questions. 

Student Learning Outcomes: By the end of the course, the student (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:

Required Textbook: Computational Intelligence: A Logical Approach, by Poole, Mackworth, & Goebel. Oxford U. Press, 1998. [Lectures from book are here]. A new version of this book is being written: Artificial Intelligence: Foundations of Computational Agents, by Poole & Mackworth. See me for instructions on accessing a rough draft of the new version for free. However, the two books are not identical and you are responsible for material covered in lecture (which may not be covered in the new version). 

Optional Textbooks/References:

Supplementary Readings: You are also responsible for reading supplementary materials handed out in class or placed on-line for the class.

Course Calendar
Note: this is a tentative schedule. It is your responsibility to check the web site for updates during the semester. Abbreviations used in calendar for readings (see above for full author and title): Computational Intelligence textbook (CI), draft of new version of textbook (AI), Bratko's Prolog book (B), Russell and Norvig's AI book (RN)
 Tu/Th dates Due Dates/Tests Textbook (CI)
Reading		 Topic this week 
Other Reading
Jan 15/17
CI 1 Introduction to AI; Logic Programming  B 1-3, RN 6-7, AI 1
Jan  22/24

Logic Programming
 B 4.3,5-7, 8.4
Jan 29/31
CI 3
 Logic Programming
 AI 5-6, B4.5, 9.1, 9.5
Feb 5/7
 HW1 due 2/5
 CI 2
 Logical Foundations
 RN 6-7, 9-10; AI 5-6
Feb 12/14
CI 4
 Search
 RN 3-4; AI 3-4
Feb 19/21 HW2 (problems 1-2) due 2/19
Search
Feb 26/28 HW 3  due 2/26, HW2 problem 3 (extra credit) due 2/26
 CI 5-6
 Knowledge-based Systems
 RN 8; AI 7-8, Coppin ch. 9
Mar 4/6
 Test 1 Mar 4 (covers  CI 1-4 & logic programming in Prolog)
KBS cont.
Mar 11/13 No class 

Spring Break
Mar 18/20
CI 9
 Default Reasoning
 AI 9
Mar 25/27
CI 10
 Reasoning under Uncertainty
 Handout: Bratko on Bayesian networks, RN 14-17, AI 10
April 1/3
 HW 4 due 4/1
Reasoning under Uncertainty - applications
 TBA
Apr 8/10 Project design due Apr 8
 CI 8
 Planning
 Handout: Bratko STRIPS planner (p. 414-21), AI 11, RN 11-13
Apr 15/17
TBA
 Selected topics (ML, NLP)
 TBA
Apr 22/24 HW 5 due 4/22
Test 2 Apr 24 (on remainder of course)
Review (4/22)
Apr 29/May 1 Project due Apr 29
Project demo (4/29 and 5/1)
May 6 No class (Friday classes meet today)



Grading
Description Points
Test 1 25
Test 2 25
HW 1 - 5
25 (total)
Project design 5
Project
15
Miscellaneous: class participation, in-class exercises,
presentation of technical paper (required for graduate students; extra credit for undergraduates)
 5

Course Policies

Attendance is required. You may be dropped from the course for missing more than six classes.

Academic Integrity:You are expected to read and follow the UNCG Academic Integrity Policy. All work should be the student's own work unless otherwise specified in the instructions for an assignment.

Distracting/disruptive behavior  is not conducive to maintaining a good classroom environment for learning. Engaging in behavior during class such as cell phone use, use of laptops for non-class-related activities, private conversations, arriving late or leaving early (unless you have made arrangements with the instructor), and other non-class related activities may result in a request to leave the classroom. Persistent behavior of this type may result in being dropped from the course (see UNCG Disruptive Behavior Policy).

Late Work: Late work on HW1-HW4 will be penalized at 2 points per day (each day ending at 5 pm, weekends and holidays included), and will not be accepted after the assignments have been graded or the solutions have been discussed in class. HW 5 is due in class and will not be accepted late. If you are unable to attend on a date when work is due it is your responsiblity to have your work delivered to the instructor on-time for credit. Scheduled graduate student presentations that are late may not receive credit.  Late work on the project will be penalized at 5 points per day and must be demoed at a time approved by the instructor in order to receive credit.

Missed exams may be taken only if the student's absence has been excused by the instructor and if the exam is made up at the make-up exam time announced by the instructor.

Disabilities: If you have any disability-related needs, please inform us as soon as possible.

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

Resources

  Prolog