Professor Harry Wechsler

Department of Computer Science

George Mason University

Fairfax, VA 22030
 
 

e-mail : wechsler@cs.gmu.edu

www: http://cs.gmu.edu/~wechsler/

(703)993-1533 (office)

(703)993-1530 (sec)

(703)993-1710 (fax)
 

GEORGE MASON UNIVERSITY

____________________________________________

SPRING 2003

CS580 - 001

Artificial  Intelligence

001 30910 W 7:20 p.m. – 10:00 p.m. R  B118

Exam1   :  Wednesday,  March 19

Exam2  :   Wednesday,   May 14

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Textbook

Artificial Intelligence : A Modern Approach by Stuart Russell and Peter Norvig,
2nd edition, Prentice Hall, 2003.

Web site: http://aima.cs.berkeley.edu/

 

Office Hours

W    6 - 7 PM  or by appointment (SITE II - Rm. 461)

TA

Shen-Shyang  Ho – rm. CS 435

 sho@gmu.edu

T and TH:  2 – 4 PM

Reference

Artificial Intelligence  (4th Edition) by  George Luger, Addison Wesley, 2002

Programming Languages

Here are some links for LISP, PROLOG  and MATLAB :

1. Getting Lisp

On osf1, there's a Lisp system called LispWorks.  If you don't like telnetting in and running Lisp :-) there are several freeware packages you can try. Several Major Lisp firms offer free ANSI-standard CLTL2 common Lisp systems:

 

Information on  Online Lisp Tutorials and Starting, Compiling, and Quitting Lisp on OSF1 is available at http://cs.gmu.edu/~sean/cs687/Lisp.html

You should be aware that there are two other variants of Lisp out there which are NOT Common Lisp. Those variants are Scheme and Emacs Lisp.

2. Getting Prolog

SWI-Prolog
http://swi.psy.uva.nl/projects/SWI-Prolog/download.html

3. Getting  MATLAB

MATLAB primer available at :

http://www.cs.gmu.edu/~zduric/cs580/primer40.ps

access to MATLAB from both CS and IT&E

for further information use 'help' and 'demo'

Course Description

The course is about the automation of intelligent behavior. We cover basic principles
and methods for intelligent (heuristic search), game playing and problem solving, 
predicate calculus and automatic reasoning, knowledge representation,
reasoning with uncertainty and belief (Bayes) networks, (symbolic, connectionist and evolutionary)
learning, natural language processing,  and Human-Computer Intelligent Interaction (HCI). 
LISP, PROLOG, and MATLAB are  the programming languages of choice used  to implement
the AI methods learned during the course. The approach used throughout the course is to address
specific intelligence tasks, motivate how to solve them, describe algorithmic solutions, and
consider comparative performance evaluation.  We learn by doing things  เ Homeworks require hands - on
experience; it includes specific programming & functional projects.

Grading

1. Homework : 50 %

Late Homework is not accepted.

Choose two out of the three projects (listed below after the tentative schedule for the class) :

Project  #1 เ due on or before  March  12 เ 25  %

Project  #2 เ due on or before  April 2  เ 25  %

Project  #3 เ due on or before  May 7   เ 25  %

 

2. EXAM1 : 25 %

March 26: closed books and closed notes; please bring examination book;

Covers : January 22 – March 12 lectures

 

2. EXAM2 : 25 %

May 14 :  closed books and closed notes; please bring examination book;

Covers :  April 9 –  May 7 lectures

 

Tentative Schedule
 

January 22

Chs. 1 and 2 : = AI.  

History and Applications.  Is the Brain a Digital Computer by J. R. Searl : http://cogsci.soton.ac.uk/~harnad/Papers/Py104/searle.comp.html

 

January 29 –

February 12

Ch. 3 – 6 : = Problem-Solving. 

Strategies for State Space Search (minmax and alpha-beta pruning), Informed and Heuristic Search Methods, Game Playing, and Constraint Satisfaction Problems, Evolutionary Computation and Genetic Algorithms.

applications: game design

individual study :  Luger / Ch. 14 : PROLOG

March 5 – March 12

Chs. 7 – 10 :=  Knowledge Representation  and Reasoning. Propositional Logic, First Order Logic and Predicate Calculus, Reasoning and Inference, General Problem Solver (GPS) and Resolution Theorem Proving, Knowledge Bases & Experts Systems, Data Abstraction, Knowledge Representation {Semantic Networks, Frames, and Conceptual Dependencies} and Ontologies /see SEMANTIC  WEB : http://www.w3.org/2001/sw/ 

applications: expert systems

individual study : Luger / Ch. 15 : LISP

March 19

 

Chs. 13 – 14 : = Uncertain Knowledge and Reasoning. Uncertainty, Bayesian Nets; Ignorance (Demster-Shafer) and vagueness (Fuzzy sets and fuzzy logic); REVIEW for EXAM 1

applications: decision-making systems

March 26

EXAM1 – CLOSED BOOKS and CLOSED NOTES

Please bring examination book !

Covers January 22  – March 12  lectures

April 2 – April 9

Chs. 18 & 20 :=  (Machine) Learning.

Symbolic – Based : Induction (The Problem of Induction at http://dieoff.org/page126.htm) Decision Trees and Conceptual Learning; Connectionist – Based:  Multi-Layer Networks & BackPropagation and Competitive Learning;  Performance Evaluation;

applications : data mining and knowledge discovery

individual study : MATLAB

April 16 - 30

Chs. 15 & 22 – 24 := Comunicating, Perceiving and Acting: HMM (Hidden Markov Models) and Speech Processing,  HCI (Human-Computer Interaction), Natural Language Processing

applications : biometrics and face recognition

applications : adaptive and intelligent interfaces; smart rooms

May 7

Chs. 26 – 27 := Conclusions; REVIEW for EXAM 2

May 14

EXAM2 – CLOSED BOOKS and CLOSED NOTES

Please bring examination book !

Covers April 2 – May 7 lectures

 

Project  # 1– due on or before March 12 :   Game Playing / CHECKERS
(use programming language of your choice) or another game of your choice

Game Rules : distributed in class.

Use intelligent search and implement an user interface to play the game.

Schedule time to have your program play against the TA or the Instructor &

Submit Short Report that includes (i) task and approach; (ii) representation, data structures,

And GUI; (iii) game strategy (look-ahead, minmax, alpha-beta,..) and evaluation function; (iv) software

tools and hardware platform; and (v) performance evaluation and conclusions.

 

Project  # 2 – due on or before  April 2    : Reasoning

Programming 1 :  Missionaries and Cannibals (use PROLOG or LISP)

Three missionaries and three cannibals are on one side of the river,
along with a  boat that can hold one or two people. Find a way to get
everyone to  the other side, without ever leaving a group of missionaries
in one place outnumbered by the cannibals in that place. Try using CSP
strategies.

OR

Programming 2 :  your choice of problem (use PROLOG or LISP)

Extra Credit (15%) for Using Both Prolog and Lisp !

 

Project  # 3 – due on or before May 7   :  Learning

Programming 1 : Classification (use MATLAB or programming language of your choice)

Access UCI repository at www.ics.uci.edu/~mlearn/MLRepository.html  and choose
some classification problem and the corresponding data sets.
Solve and implement the classification task using
DT (Decision Trees). Discuss your results.  For extra credit  (15%) solve and implement the
same classification task using backpropagation (BP) and make a comparison against the
results obtained using DTs.