Professor Harry Wechsler
Department of Computer Science
e-mail : wechsler@cs.gmu.edu
www: http://cs.gmu.edu/~wechsler/
(703)993-1533 (office)
(703)993-1530 (sec)
(703)993-1710 (fax)
____________________________________________
SPRING 2004
Artificial Intelligence
001 00952 W
Office Hours
W
Teaching Assistant
Shen-Shyang Ho, sho@gmu.edu, SITE II – Rm. 435 (Faculty
Reading Room – not the printer room) MO
Gabriel Balan, gbalan@cs.gmu.edu,
SITE II – Rm. 365,
MO
Textbook
Artificial
Intelligence: A Modern Approach by Stuart Russell and Peter Norvig,
2nd
edition, Prentice Hall, 2003.
Web site: http://aima.cs.berkeley.edu/
http://aima.eecs.berkeley.edu/slides-pdf/
Reference -
Artificial
Intelligence (4th Edition) by
George Luger, Addison Wesley, 2002
Course
Description
The course is about
the automation and learning of intelligent behavior. We cover basic principles
and methods for intelligent search and problem solving, game
playing, and constraint satisfaction problems (CSP), knowledge representation, predicate calculus /
first-order logic and automatic reasoning (resolution with refutation),
reasoning with uncertainty and belief (Bayesian) networks, (symbolic,
connectionist and evolutionary) learning, and natural language processing [communication].
LISP, PROLOG, and MATLAB are the AI
programming languages of choice used to implement the 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 undertake comparative performance evaluation.
Programming
Languages
Here are some links for LISP, PROLOG and MATLAB :
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:
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://aima.cs.berkeley.edu/ai.html#prolog
3.
Getting MATLAB
MATLAB primer available at:
http://www.math.utah.edu/lab/ms/matlab/matlab.html
access to MATLAB from both CS and IT&E
for further information use 'help' and 'demo'
Grading
1.
Homework: 50 %
You have to submit Project
#1 and one of Projects #2 or #3 (described below after the tentative schedule
for the class). You have to use at least one of the AI programming languages on
the projects you choose.
Project
#1 à due on or before March 24 à 25 %
Project
#2 à due on or before April 7 à 25 %
Project #3 à due on or before April 28 à 25 %
2.
EXAM#1: March 17 à 25 %
3.
EXAM#2: May 5 à 25 %
Tentative
Schedule
|
January 21 |
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 28 - February 11 |
Ch. 3 – 6:
= Search and Problem-Solving. Strategies for State Space Search (minmax
and alpha-beta pruning), Informed and Heuristic Search Methods, Game Playing,
Constraint Satisfaction Problems (CSP), Evolutionary Computation and Genetic
Algorithms. applications: game design LISP: (reference: Luger / Ch. 15) |
|
February 18 – March 3 |
Chs. 7 – 9 := Logic and Reasoning. Propositional
Logic, First Order Logic and Predicate Calculus, Reasoning and Inference,
General Problem Solver (GPS) and Resolution Theorem Proving. REVIEW for EXAM 1 PROLOG:
(reference: Luger / Ch. 14) |
|
March 17 |
EXAM#1 – CLOSED BOOKS and CLOSED NOTESPlease bring the
blue examination book! Covers January 21 – March 3 lectures. |
|
March 24 – April 7 |
|
|
April 14 – April 21 |
Chs. 13 – 14: = Uncertain(ty) Knowledge and Reasoning. Uncertainty and Bayesian Nets. applications: decision-making systems |
|
April 21 – April 28 |
Chs. 23 := Communication Natural
Language Processing; Chs. 26 – 27
:= Conclusions; REVIEW
for EXAM 2 |
|
May 5 |
EXAM#2 – CLOSED BOOKS and CLOSED NOTESPlease bring the
blue examination book! Please bring scientific calculator with logarithmic function Covers March 24 –April 28 lectures. |
Project # 1– due on or before
March 24: Search
and Problem Solving / Game Playing / CHECKERS or
another game of your choice/ Use programming language of your choice/
Game
Rules:
distributed in class.
Use intelligent
search and implement a user interface to play the game.
Schedule time to
have your program play against the Instructor or TA &
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)
information on software tools used and hardware platform; and (v) performance
evaluation and conclusions.
Project # 2 – due on or
before April 7: Knowledge
Representation and Reasoning
Programming
1: Missionaries and
Cannibals / Use LISP or PROLOG or both for extra 15 % credit /
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 LISP or PROLOG or both for extra 15% credit /
Project # 3 – due on or
before April 28: Learning
Programming
1:
Classification / Use MATLAB /
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 DT.