CS 540 Intro to AI
section 2
1:00-2:15 Tue / Thur
Room 1325 CS&S

Administrative Details

Lecturer: Louis Oliphant

Office: 5390 CS

Phone: 262-0018

Email: oliphant@cs.wisc.edu

Hours: TR 2:30 – 4:00 PM

TA: Voon-Fee Yong

Office: 5364 CS

Email: yong@cs.wisc.edu

Hours: MW 2:00-3:00 PM

Administrative Details

Mailing List

mailing list: compsci540-2-f05@wisc.edu

Course home page:

http://www.cs.wisc.edu/~cs540-2

Textbook: S. Russell and P. Norvig

Artificial Intelligence: A Modern Approach

Prentice Hall, 2003, Second Edition

Administrative Details

Prerequisites

CS302 or Java programming experience

CS367 or Data structures experience

Grading

Homeworks ~45%

Project ~ 15%

Midterm ~ 15%

Final ~25%

Homeworks

5 homework assignments

Written and programmed portions

Written handed in at beginning of class

Programs handed in electronically

Only turn in source code

Programming in Java

3 late days to be used anytime throughout semester after that 10% off each day (max 3 days late on any assignment)

Assignments are to be done individually

Attend Unix orientation of you don't know Unix

Projects

Do in groups of 3 to 4

Dig deep into topic not covered in class

Can involve programming + lab report (3 pages)

or Written report (5 pages)

15 minute presentation at end of semester

More on this later

Exams

Midterm and Final

Dates:

Midterm around Nov 1st 7:00-9:00pm

Final Dec 19th 10am-12noon

If you have a conflict with these dates/times see me to reschedule

First Assignment

Read Chapters 1 and 2 in Russell and Norvig

Email me with the following info:

Name

Major

Year in school

Why you are taking the course

What you hope to get out of the course

A picture of yourself

(use Camera Kiosk in room 1359 if needed)

Syllabus

Week 1:	-	Intro to AI, Agents

Week 2:	-	Uninformed Search

Week 3:	-	Informed Search, Escaping Local Maxima

Week 4:	-	Game Playing

Week 5:	-	Logical Agents

Week 6:	-	First Order Logic

Week 7:	-	Inference in FOL, Prolog

-------------------------Midterm------------------------------------------

Week 8:	-	Decision Trees

Week 9:	-	Perceptron

Week 10:	-	Neural Networks

Week 11:	-	Uncertainty

Week 12:	-	Bayesian Networks

Week 13:	-	Markov Models

Week 14:	-	Project Presentations

Week 15:	-	Project Presentations/Conclusions

Introduction to
Artificial Intelligence

What is intelligence?

The capacity to acquire and apply knowledge.

The faculty of thought and reason.

The ability to learn or understand or to deal with new or trying situations.

Introduction to
Artificial Intelligence

What is Artificial Intelligence?

The textbook advocates “acting rationally”

Thinking humanly

Thinking rationally

Acting humanly

Acting rationally

Acting humanly: Turing Test

Turing (1950) "Computing machinery and intelligence":

"Can machines think?"  "Can machines behave intelligently?"

Operational test for intelligent behavior: the Imitation Game

Predicted that by 2000, a machine might have a 30% chance of fooling a lay person for 5 minutes

Anticipated all major arguments against AI in following 50 years

Suggested major components of AI: knowledge, reasoning, language understanding, learning

Check out http://cogsci.ucsd.edu/~asaygin/tt/ttest.html

Thinking humanly: cognitive modeling

1960s "cognitive revolution": information-processing psychology

Scientific theories of internal activities of brain

Validation Requires:

Predict and test behavior of humans (top-down)

Identification from neurological data (bottom-up)

Both approaches, Cognitive Science and Cognitive Neuroscience, distinct from AI

Thinking rationally: “laws of thought”

Aristotle: what are correct arguments/thought processes?
“Socrates is a man”
“All men are mortal”
“Therefore Socrates is mortal”

Logical systems developed for rational deduction and inference

syntax

semantics

Problems

Not all intelligent behavior is mediated by logical deliberation

Big difference in solving problems “in theory” and in practice

Acting rationally: rational agent

Rational behavior: doing the right thing

The right thing: that which is expected to maximize goal achievement, given the available information

Doesn't necessarily involve thinking – e.g., blinking reflex – but thinking should be in the service of rational action

AI prehistory

Philosophy	syllogism, boolean logic, first order logic, induction

Mathematics	Formal representation and proof algorithms,
computation, (un)decidability, (in)tractability,
probability

Economics	utility, decision theory, game theory

Neuroscience	physical substrate for mental activity

Psychology	phenomena of perception and motor control,
experimental techniques

Computer	building fast computers
engineering

Control theory	design systems that maximize an objective
function over time

Linguistics	knowledge representation, grammar

Abridged history if AI

1943	McCulloch & Pitts: Boolean circuit model of brain

1950	Turing's "Computing Machinery and Intelligence"

1956	Dartmouth meeting: "Artificial Intelligence" adopted

1952—69	Look, Ma, no hands!

1950s	Early AI programs, including Samuel's checkers
program, Newell & Simon's Logic Theorist,
Gelernter's Geometry Engine

1965	Robinson's complete algorithm for logical reasoning

1966—73	AI discovers computational complexity
Neural network research almost disappears

1969—79	Early development of knowledge-based systems

1980--	AI becomes an industry

1986--	Neural networks return to popularity

1987--	AI becomes a science

1995--	The emergence of intelligent agents

Major Subdivisions of AI

Understanding

Thinking

Acting

AI: Understanding

Computer Vision – understanding what you see

Natural Language Processing – understanding the written (spoken) word

AI: Thinking

Capturing Structure and Reaching Goals

Machine Learning

Planning

Clustering

AI: Acting

Robotics

Mars Rover	RoboSoccer

State of the art

Deep Blue defeated the reigning world chess champion Garry Kasparov in 1997

No hands across America (driving autonomously 98% of the time from Pittsburgh to San Diego) http://www.cs.cmu.edu/afs/cs/user/tjochem/www/nhaa/nhaa_home_page.html

Logistics and planning of 1991 Gulf War involved up to 50,000 vehicles, cargo, and people

NASA's on-board autonomous planning program controlled the scheduling of operations for a spacecraft: http://www.stsci.edu/hst/HST_overview/

Proverb solves crossword puzzles better than most humans
http://oneacross.com/, http://puzzles.usatoday.com/

Recommendations at on-line shopping sites

Just where are we now? http://www.captcha.net/

Consider AI use in one company

Search

Page Rank –Huge Graph Search Problem

Sponsered Links

Sponsered Ads: Relevance and Money

Google News

Cluster Common Articles

Google maps

Search Problem

Conclusions

AI is big business

Still can't do most things

What it can do it does extremely well

Major Subdivision of AI

vision and language

robotics

machine learning

First Assignment (reminder)

Read Chapters 1 and 2 in Russell and Norvig

Email me with the following info:

Name

Major

Year in school

Why you are taking the course

What you hope to get out of the course

A picture of yourself

(use Camera Kiosk in room 1359 if needed)

2005-08-17T16:06:16