CS 580 - Spring 2013

Introduction Artificial Intelligence 12449 CS 580 - 001

Instructor:  Prof. Harry Wechsler wechsler@gmu.edu

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.

 

Main Topics: Problem Solving, Search, Representation and Inference, Uncertainty and Probabilistic Reasoning, Learning, and Communication (Perception and Natural Language Processing).

 

Time, Day, and Venue: R Thursday, 4:30 pm - 7:10 pm

Innovation Hall 133

http://registrar.gmu.edu/calendars/2013Spring.html

First day of classes: Thursday, January 24

Spring Break [March 11 17]: no class on Thursday, March 14

Last day of classes: Thursday, May 2

http://registrar.gmu.edu/calendars/2013SpringExam.html

FINAL Exam: Thursday, May 9, 4:30 7:15 pm

Office Hours: Thursday, 3:00 pm 4:00 pm (ENGR - 4448)

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/

Tentative Schedule:

 

1/24 1/31: 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}; LISP

 

2/7 2/14: Uninformed and Informed (Heuristic) Search (Chapters 3 4); PROLOG and MATLAB; WHITE PAPER for TERM PROJECT (due February 7)

 

2 /21: Constraint Satisfaction (Chap. 5) and Planning (Chap. 10)

 

2/ 28: Game Playing (Chap. 6)

 

3/7: REVIEW for MIDTERM

 

3/14: Spring Break

 

3/21: MIDTERM (covers Chapters 1 6) (closed books and notes)

 

3/28: Knowledge and Reasoning (Chap. 7)

 

4/ 4: First-Order Logic: Representation and Inference (Chapters 8 9)

 

4/11: Uncertainty / Probability / Bayes and Inference Using Belief Networks (Chapters 13 14)

 

4/18: Learning / Decision Trees and Ensemble Learning (Chap. 18)

 

4/25: Communication / Natural Language Processing and Perception / (Chapters 22 24)

 

5/2: REVIEW for FINAL

 

5/9: FINAL (cumulative) (closed books and notes)

 

 

Grading:

        Homework: 20%

        Term Project (due April 25): 20%

        MIDTERM: Thursday, March 21 20 %

        FINAL : Thursday, May 12 40 %

Honor Code

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