CSC 380/480 - Foundations of Artificial Intelligence - Winter 2007
General
Course Information
Instructor:
Bamshad
Mobasher
Email: mobasher@cs.depaul.edu
Office: Loop Campus, CTI Building, Room 833
Phone: (312) 362-5174
Office Hours: Monday. 4:30-5:30, Tuesday. 4:00-5:30 PM (or by
appointment)
Course Objectives:
This course will provide an in-depth survey of important concepts,
problems, and techniques in Artificial Intelligence. A particular focus
and a unifying theme in the course will be the concept of "intelligent
agents". No previous knowledge of AI is necessary to take the course.
The course is particularly suitable for graduate and advanced
undergraduate students who want to gain the technical background
necessary to build intelligent systems, or as a preparation for more
advanced work in AI. The concepts and techniques learned in this course
will be directly applicable to many other areas of computing sciences,
including software design, distributed systems, databases, and
information management and retrieval.
Textbook:
Prerequisites:
CSC 383 or 393 (or equivalent background in data structures and algorithms)
Grading Policy:
The final grade will be determined based on the following
components:
Assignments & Exams:
There will be 4-5 assignments during the quarter. These assignments
will generally be comprised of written problems, but may include some
programming components. Unless otherwise specified, late assignments
will be penalized 10% per day (with weekends counting as one day).
The students will have the option of taking a final exam
or completing a programming project which will be due at the end of the
quarter. The exam will be open book and open notes. In general, make-up exams
will only be given with prior approval or in cases of emergencies. More information about the project
and exam will be provided later in the
quarter.
Tentative List of Course Topics
Topics |
Reading |
Introduction to AI; Intelligent Agents |
Ch. 1, 2 |
Problem Solving and Search |
Ch. 3 |
Heuristic Search |
Ch. 4 |
Logic and Knowledge Representation |
Ch. 7, 8, 9, 10 |
Basic Planning |
Ch. 11 |
Reasoning with Uncertainty; Probabilistic Reasoning |
Ch. 13, 14 |
Machine Learning |
Ch. 18 |
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