Artificial Intelligence II:
Machine Learning and Adaptive Systems
- Dr. Dennis Bahler
- Phone: 919 515 3369
- Fax: 919 515 7896
- Email: firstname.lastname@example.org
- Office: 216A Withers Hall
- Office Hours: Tuesday/Thursday 1430-1600, or by appointment
- Teaching Assistant
If you have a technical or administrative question that might be of interest to
other members of the class, please either ask during class or use the course
Otherwise, bring your question to the instructor during office hours.
I am also highly available via email.
Please include CSC 720 in the subject line.
Class Time: Tuesday and Thursday 1305-1420
Place: 222 Withers Hall
Course Locker: /afs/eos/courses/csc/csc720/
This is a seminar and project course in advanced
artificial intelligence, in particular on
intelligent computer systems which learn, i.e., adapt their behavior through experience,
and system capable of dealing with uncertainty or approximation.
The course will focus on readings, discussion, and student presentations
interspersed with lectures by the instructor.
Readings will come from the technical literature.
Tentative Course Outline
Course topics will be chosen from among:
Decision Tree Induction,
Neural Network Models,
Genetic Classifier Systems,
Version Space and Candidate Elimination,
Inductive Logic Programming,
Induction of Bayesian Models from Examples,
Unsupervised Concept Formation,
The Biology of Learning,
Learnability Theory and PAC Learning,
Automating Knowledge Acquisition.
To acquaint students with the current state of research in selected areas
of artificial intelligence through reading and discussion of relevant
Areas of special interest this semester are machine learning, artificial
neural models, and other adaptive systems.
To enable students to develop and synthesize their own and others' ideas
relating to some aspect of artificial intelligence
(not necessarily one of the areas explicitly covered in class)
in the form of either a major
paper (20-25 pages) or a significant programming project.
CSC 520 (Artificial Intelligence I) or the equivalent or permission of instructor.
Letter grades will be assigned using the plus-minus scale.
Grading will be based on a weighted combination of the following elements:
ATTENDANCE, CLASS PARTICIPATION, PRESENTATIONS, etc.
Active participation in class discussion is ESSENTIAL for success in
STUDENTS WILL BE EXPECTED TO HAVE READ THE ASSIGNED MATERIAL IN ADVANCE OF
Each student will be responsible for leading the class from time to time by
presenting one or more related papers and initiating the discussion.
SHORT QUIZZES (10%):
Students will be expected to have read the material in advance of class.
Each presenting student is required to write a short (1 page, 5- to 8-minute)
quiz covering the day's reading.
All students will take these quizzes, including authors.
Grading will be done by the instructor.
The author's answers, provided they are adequate, will constitute the
answer key for each quiz.
PROJECT and/or PAPER (50%):
Either (i) a major paper (20-25 pages)
fully annotated with references to the literature as appropriate,
or (ii) a project requiring significant programming in some area of
Projects will require a descriptive writeup and extensive program documentation
as well as the code itself.
Topics of papers and/or projects must be approved in advance by the instructor.
All students will present their projects or papers orally at
the end of the course.
Time permitting, there may also be progress reports mid-semester.
FINAL EXAM (10%):
There will be a comprehensive final exam on the readings at the conclusion
of the course.
There is no textbook for this course.
Readings will be made available.
A student shall be guilty of a violation of academic integrity if he or she
represents the work of others as his or her own or aid another's misrepresentation.
Any violation associated with an examination or quiz will result in a failing grade for the course.
Project related offenses may incur a reduction of up to two letter grades.
Such violations will be reported to the Office of Student Conduct, which may
impose penalties beyond those by the instructor.
Students with Diabilities
If you have a disability that may affect your participation in this class, please
notify the instructor.
Students requiring extra time for examinations and quizzes are asked to make
arrangements at least three days in advance.
You may contact the NCSU Disability Services for Students Center regarding campus
services at the Student Health Center for more information and assistance.