CS 580
Artificial Intelligence

Time/Location: Wednesday 4:30-7:10pm, Online, Blackboard Collaborate  
Instructor: Jana Kosecka
Office hours:  2-3pm Wednesday
Contact: Office 4444 Research II, e-mail: kosecka@gmu.edu, 3-1876
Course web page: http://www.cs.gmu.edu/~kosecka/cs580/
Course Communication: Piazza

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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.