Instructor: Prof. Harry
Wechsler wechsler@gmu.edu
Email correspondence: from GMU accounts with subject: CS 580
Course Description
– Principles
and methods for knowledge representation, reasoning, problem solving, planning,
heuristic search, reasoning, learning, probabilistic reasoning, and natural
language processing and their application to building intelligent systems in a
variety of domains. LISP, PROLOG, MATLAB, or
expert
system programming language.
Prereq: CS 310 and CS 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.
Time, Day, and Venue: R – Thursday, 4:30
pm - 7:10 pm
Innovation
Hall 134
Office Hours: R – Thursday, 3:15 – 4:15 pm or by appointment, ENGR 4448.
http://registrar.gmu.edu/calendars/spring-2015/
First day of classes: Thursday, January 22
Spring break: no class on Thursday, March 12
Last day of classes: Thursday, April 30
http://registrar.gmu.edu/calendars/spring-2015/final-exam/
FINAL Exam: Thursday, May 7, 4:30 – 7:15 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.
Week1:
Introduction to AI (Chap.1) & Intelligent
Agents and Problem Solving (Chapter 2) & Philosophical Foundations (Chap.
26) & AI: Present and Future (Chap. 27); AI = Rational Problem Solving
{Search, Reasoning, Learning, Communication}; Bayes; LISP
Week2: Uninformed and Informed (Heuristic) Search
(Chapters 3 – 4); MATLAB; Metrics and Performance Evaluation; WHITE PAPER for
TERM PROJECT (due February 5)
Week3:
Adversarial Search and Game Playing (Chap. 5)
Week4:
Constraint Satisfaction (Chap. 6) and Planning (Chap. 10)
Week5:
Catch – Up and REVIEW for MIDTERM
Week6:
MIDTERM (covers Chapters 1 – 6) (closed books and notes)
Week7:
Knowledge and Reasoning (Chapters 7 and 8)
3/12:
Spring Break
Week8:
First-Order Logic: Representation and
Inference (Chapters 8 and 9)
Week9:
Biometrics and Face Recognition
Week10:
Learning / Decision Trees and Ensemble Learning / AdaBoost (Chap. 18) and Data Mining
Week11:
Uncertainty / Probability / Bayes and Inference Using Belief / Bayes Networks
(Chapters 13 – 14)
Week12:
Communication / Perception and Natural Language Processing / (Chapters 22 – 24)
and Deep Learning
Week13:
Term Project Presentations and Discussion
Week14:
REVIEW for FINAL
·
Homework: 20%
·
Term Project (due April 23): 25%
·
MIDTERM:
Thursday, February 26 – 25
%
·
(cumulative)
FINAL : Thursday, May 12 – 30 %
You are expected to abide by the GMU honor
code. Homework assignments and exams are individual efforts. Information on the
university honor code can be found at http://academicintegrity.gmu.edu/honorcode/.
Additional departmental CS information: http://cs.gmu.edu/wiki/pmwiki.php/HonorCode/CSHonorCodePolicies