CS 451/551: Artificial Intelligence
Course Syllabus -- Spring 2001

Professor: Janice T. Searleman
Office: 375 Science Center
Phone: 268-2377
E-mail: jets@clarkson.edu

Office Hours: MW 3:00-4:00; Tu 11:00-12:00; Th 2:00-3:00; F 1:00-2:00. If you cannot come during these scheduled office hours, feel free to contact me to set up an appointment.

Course Objective: This course is a comprehensive introduction to core concepts in artificial intelligence (AI), and surveys active research areas. Topics covered include:

Text and Software: Grading Policy:

You are responsible for all material discussed in class and in the reading assignments. Attendance is particularly important, and class participation is encouraged. Written homework and programming assignments are expected to be individual efforts, and are due in class on the date posted. Late programs will be accepted up to one week late, but there will be a 15% deduction in grade.

The project allows you to explore in more depth an area of AI, such as natural language understanding, computer vision, intelligent tutoring systems, neural networks, or whatever you find most interesting. You may work in teams of two on a project of sufficient scope, as approved by the instructor. A brief proposal describing your project is due on Friday, February 23, and the project itself is due on Friday, April 27. You are required to demonstrate your project to the instructor during the last week of class.

Tentative Course Outline: Chapters 18 & 20
Introduction to AI
   The Turing Test; Intelligent Agents
Chapters 1 & 2
Problem Solving
   State-Space Search; Heuristic Search; Game Playing
Chapters 3, 4 & 5
Knowledge & Reasoning
   Predicate Calculus; Inference; Forward & Backward Chaining;
   Resolution; Frame Systems and Semantic Nets
Chapters 6, 7, 9 & 10
   Planning Agents; Situation Spaces

Chapter 11
Reasoning Under Uncertainty
   Probabilistic Reasoning; Belief Networks; Decision Making
Chapters 14, 15 & 16
Learning & Neural Nets
   Inductive Learning; Decision Trees;
   Feedforward networks; Backpropagation
Advanced Topics
   Natural Language Understanding; Perception; Speech Recognition
Chapters 22, 24 & 26
We will do the first three topics in detail, and only lightly cover the last four.

Last modified: 12 January 2001