Artificial Intelligence


Instructor Textbook Schedule Course Work Assignments Labs Deadlines Grading

The field of artificial intelligence includes two distinct foci: the understanding of human intelligence and the development of computer programs to solve problems in non-traditional ways. The first of these emphasizes theoretical models, while the second draws upon various problem-solving strategies, algorithms, and data representations to solve specific problems. While the component of artificial intelligence that falls within computer science touches upon some theoretical models of human intelligence and behavior, more attention is paid to problem-solving strategies and the building of systems.

This course provides a framework for considering multiple approaches for storing and processing symbolic data. The course builds upon concepts and algorithms from previous CS courses, developing alternative perspectives of topics studied earlier and introducing new approaches. Within the course, students will apply general principles and techniques to solve sample problems.

Instructor

Henry M. Walker
Office: Science 2420
Telephone: extension 4208
E-mail: walker@math.grin.edu

Office Hours are posted weekly on the bulletin board outside Science 2420, with additional hours possible by appointment. You may reserve a half hour meeting by signing up on the weekly schedule, but please sign up at least a day in advance.

Textbooks

Thomas Dean, James Allen, and Yiannis Aloimonos, Artificial Intelligence: Theory and Practice, Benjamin/Cummings Publishing Company, Inc., 1995.

Course Work

This course will involve written assignments, programming assignments, projects, and tests.

  1. Written Assignments: Written exercises will be assigned to clarify and expand upon ideas and techniques described in class or covered in the text.

  2. Programming Assignments: Since LISP is the prevalent programming language for AI research, the course will include an introduction to LISP programming. Several programming problems will be assigned through the semester to help students become comfortable with LISP.

  3. Projects: To clarify general approaches and specific techniques, students will choose a problem for solution. Then, students will investigate their problem from the perspective of both rule-based systems and neural networks.

  4. Hour Test: Following the Tentative Class Schedule, a one-hour test is scheduled for Wednesday, February 25.

  5. Exam: Following the published exam schedule, an exam is scheduled for 9:00 am on Thursday, May 14, during exam week.
Deadlines

Late Penalty: Work is due at the start of class on the date specified in the assignment. A penalty of 33 1/3 % per class meeting will be assessed on any work turned in late, even work submitted at the end of a class. Thus, work turned in 4 days late will be weighted -33 1/3 %; since a negative score reduces a semester total, it is better not to turn the work in at all.
Exception: Deadlines for programming problems and projects are automatically extended at least one class day if the HP network is down for an unscheduled period of 3 or more hours during the week preceding the assignment due date. (In such cases, however, deadlines for written assignments are not extended.)

Absolute Deadline: All homework must be turned in by Friday, May 8 at 5:00 pm.

Collaboration

The work in this course is split between individual and group work. Students are encouraged to work together on written assignments. However, since this course seeks to develop individual understanding and mastery as well, collaboration is not allowed on programming assignments, projects, or tests.

Grading

This instructor's grading philosophy dictates that the final grade should ultimately be based upon each student's demonstration of his or her understanding of the material, not on the performance of the class as a whole nor on a strict percentile basis. The following scheme is proposed as a base for how the various assignments, projects, and tests will be counted in the final grade. These percentages may be adjusted according to the actual work involved in each type of activity.
Written Assignments: 25% Test 10% Exam: 25%
Programming Assignments: 15% Project: 25%


This document is available on the World Wide Web as

http://www.math.grin.edu/~walker/courses/261/

created January 3, 1998
last revised January 16, 1998