CS 480 - Fall 2015

Intro Artificial Intelligence CRN: 70383 CS 480 - 001

Instructor:  Prof. Harry Wechsler wechsler@gmu.edu

Email correspondence: from / to GMU accounts with subject: CS 480

Course Description Principles and methods for knowledge representation, reasoning, learning, problem solving, planning, heuristic search, natural language processing, and their application to building intelligent systems in a variety of domains. Uses LISP, PROLOG, MATLAB, or expert system programming language.


Prerequisite: Grade of C or better in CS 310 and 330


Main Topics: Problem Solving, Search, Knowledge and Reasoning, Uncertainty and Probabilistic Reasoning, Learning, and Communication (Perception / Vision and Natural Language Processing). Additional topics time permitting: Data Mining, Deep Learning, and Biometrics.


    Knowledge of and ability to apply uninformed and heuristic search methods;

    Knowledge of and ability to apply knowledge representation and reasoning methods based on first-order logic;

    Knowledge of and ability to apply basic probabilistic reasoning methods;

    Knowledge of and ability to apply basic machine learning methods;

    Ability to implement basic AI methods in Lisp, Prolog or a knowledge-based systems development environment;

    Ability to identify and apply basic AI methods to a given problem.


Time, Day, and Venue: TR Tuesday and Thursday, 3:00 pm 4:15 pm, Innovation Hall 204

Office Hours: TR 2:00 pm 2:45 pm or by appointment, ENGR 4448.


First day of classes: T, September 1, 2015

No class on T, October 13, 2015 (Columbus Day recess) and R, November 26, 2015 (Thanksgiving recess)

Last day of classes: R, December 10, 2015


Final Exam: R, December 17, 2015, 1:30 pm  4:15 pm 
Textbook: Artificial Intelligence: A Modern Approach, Russell and Norvig (3rd ed.), Prentice Hall, 2010.
Textbook Website: http://aima.cs.berkeley.edu/
Textbook Slides: http://aima.eecs.berkeley.edu/slides-pdf/
Complementary Textbook: ANSI Common LISP, Paul Graham, Prentice Hall, 1995 http://www.paulgraham.com/onlisptext.html 


Grading Composition (100 points)

                     Homework 40 % // late homework not accepted //

                     Midterm (Tentative) R, October 15, 2015 20 %

                     (Cumulative) Final December 16, 2015 - 40 %

Grading Scale


Computing Resources


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Honor Code

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