CS 580
Artificial Intelligence
Time/Location: Wednesday
4:30-7:10pm, Exploratory Hall L004
Instructor: Jana Kosecka
Office hours: 2-3pm Tuesday
Contact: ENGR 4444, e-mail:
kosecka@gmu.edu, 3-1876
Course web page:
http://www.cs.gmu.edu/~kosecka/cs580/
Course Communication:
Piazza
This course
introduces core concepts and algorithms in Arificial Intelligence.
We will cover basic principles of search, constraint satisfaction,
decision making under uncertainty, reasoning and machine learning.
Applications of these methods in computer vision, robotics and
natural language processing will be discussed. AI is a
breadth-oriented field, and the goal of this course is to provide
the student with the foundations of the field.
The course will comprise of lectures by
the instructor, homeworks, final exam and the final project.
Prerequisites:
A working knowledge of computer systems and several programming
languages is required. The material covered in CS 310 (or INFS 519)
and CS 330 (or CS 530) as well as general computer science maturity
is assumed and used throughout the course.
Programming assignments will be in Python.
Required Textbook:
Russel and Norvig: Artificial Intelligence: A Modern Approach, 3rd edition
Grading:
Homeworks/Projects: 40%
Midterm Exam: 25%
Final Exam: 35%
Academic Integrity:
The integrity of the University community is affected by the
individual choices made by each of us. GMU has an Honor Code
with clear guidelines regarding academic integrity. Three
fundamental and rather simple principles to follow at all times
are that: (1) all work submitted be your own; (2) when using the
work or ideas of others, including fellow students, give full
credit through accurate citations; and (3) if you are uncertain
about the ground rules on a particular assignment, ask for
clarification. No grade is important enough to justify academic
misconduct. Plagiarism means using the exact words, opinions, or
factual information from another person without giving the
person credit. Writers give credit through accepted
documentation styles, such as parenthetical citation, footnotes,
or endnotes. Paraphrased material must also be cited, using MLA
or APA format. A simple listing of books or articles is not
sufficient. Plagiarism is the equivalent of intellectual robbery
and cannot be tolerated in the academic setting. If you have any
doubts about what constitutes plagiarism, please see me.
CS department Honor Code can be found here.