CS 332: Introduction to AI
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CS 332: Introduction to AI Class Hour: Section 1: MWF 1:10PM - 2:00PM. Hyer 210 PowerPoint PPT Presentation


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CS 332: Introduction to AI Class Hour: Section 1: MWF 1:10PM - 2:00PM. Hyer 210. A little bit about the instructor. Associate professor at UWW. Graduated from the University of Connecticut (05 Class), Ph.D in Computer Science and Engineering.

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CS 332: Introduction to AI Class Hour: Section 1: MWF 1:10PM - 2:00PM. Hyer 210

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Cs 332 introduction to ai class hour section 1 mwf 1 10pm 2 00pm hyer 210

CS 332: Introduction to AI

Class Hour:

Section 1: MWF 1:10PM - 2:00PM. Hyer210


A little bit about the instructor

A little bit about the instructor

Associate professor at UWW

  • Graduated from the University of Connecticut (05 Class), Ph.D in Computer Science and Engineering

  • Master of Computer Science from UW-Milwaukee (96-99)

  • Bachelor of Science from Hanoi University of Technology (86-91)


A little bit about the instructor1

A little bit about the instructor

  • Research Experience:

    • AI, User Modeling, Information Retrieval, Decision Theory, Collaborative Filtering, Human Factors

  • Teaching Experience:

    • MCS 231, 220, COMPSCI 172, 173, 222, 181, 271, 322, 381 at UWW

    • Introductory courses at UOP and Devry

    • TA for Computer Architecture, OO Design, Compiler, Artificial Intelligence


Contact information

Contact information

[email protected]

(fastest way to contact me)

MG 106

Office Hours: 9am – 10:45am MWF, noon – 1pm W, 9-10am online on skype (Tuesday) or by appointment

262 472 5170


Course objectives

Course Objectives

  • Given a basic Artificial Intelligence(AI) problem such as search, gaming, planning, machine learning, understand the theory, and implement algorithms being used to solve this problem.

  • Given a real world problem, be able to identify the parts in which AI techniques can be applied.


Technology requirement

Technology Requirement

  • Either Java Development Kit (JDK) Or C++ (Linux version).

  • Weka (machine learning): http://www.cs.waikato.ac.nz/ml/weka/

  • Genie/Smile (free download for Bayesian networks) from http://genie.sis.pitt.edu/


Book requirement

Book requirement

  • Artificial Intelligence: A Modern Approach (3rd Edition) (Prentice Hall Series in Artificial Intelligence). 2009. ISBN: 0136042597


Evaluation

Evaluation


Evaluation1

Evaluation


What is artificial intelligence

What is Artificial Intelligence?


Main topics

Main topics

  • What is AI?

  • A brief history.

  • The State of the Art.


What is ai

What is AI

  • http://www.youtube.com/watch?v=eq-AHmD8xz0

  • Discussion


Ai systems are

AI systems are ….

  • Choose all that best describe AI systems:

    • Systems that think like humans

    • Systems that think rationally

    • Systems that act like humans

    • Systems that act rationally

    • Systems that make decisions for humans

    • Systems that play with humans


Acting humanly

Acting humanly

  • Turing (1950) “Computing machinery and intelligence": Can machines think?“ “Can machines behave intelligently?” Operational test for intelligent behavior: the Imitation Game

  • http://www.youtube.com/watch?v=jq0ELhpKevY

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


Thinking humanly

Thinking humanly

  • 1960s “cognitive revolution": information-processing psychology replaced prevailing orthodoxy of behaviorism.

  • Requires scientic theories of internal activities of the brain

  • What level of abstraction? “Knowledge" or “circuits"?

  • How to validate? Requires

    • 1) Predicting and testing behavior of human subjects (top-down)

    • or 2) Direct identification from neurological data (bottom-up)

  • Both share with AI the following characteristic:

    • the available theories do not explain (or engender) anything resembling human-level general intelligence


Thinking rationally laws of thought

Thinking rationally: Laws of Thought

  • Normative (or prescriptive) rather than descriptive

  • Direct line through mathematics and philosophy to modern AI

  • Problems:

    • 1) Not all intelligent behavior is mediated by logical deliberation

    • 2) What is the purpose of thinking? What thoughts should I have out of all the thoughts (logical or otherwise) that I could have?


Acting rationally

Acting rationally

  • 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 but thinking should be in the service of rational action


Supporting fields

Supporting fields

  • Philosophy logic, methods of reasoning, mind as physical system, foundations of learning, language, rationality

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

  • Psychology adaptation, phenomena of perception and motor control, experimental techniques (psychophysics, etc.)

  • Economics formal theory of rational decisions

  • Linguistics knowledge representation, grammar

  • Neuroscience plastic physical substrate for mental activity

  • Control theory homeostatic systems, stability, simple optimal agent designs

  • Control theory homeostatic systems, stability, simple optimal agent designs


History of ai

History of AI

  • 1943 McCulloch & Pitts: Boolean circuit model of brain

  • 1950 Turing's “Computing Machinery and Intelligence“

  • 1950s Early AI programs, including Samuel's checkers program,

  • Newell & Simon's Logic Theorist, Gelernter's Geometry Engine

  • 1956 Dartmouth meeting: Articial Intelligence" adopted

  • 1965 Robinson's complete algorithm for logical reasoning

  • 1966-74 AI discovers computational complexity

  • Neural network research almost disappears

  • 1969-79 Early development of knowledge-based systems

  • 1980-88 Expert systems industry booms

  • 1988-93 Expert systems industry busts: \AI Winter"

  • 1985-95 Neural networks return to popularity

  • 1988 Resurgence of probability; general increase in technical depth, Nouvelle AI": ALife, GAs, soft computing

  • 1995: Agents, agents, everywhere : : :

  • 2003: Human-level AI back on the agenda


State of the art

State of the art

  • Which of the following can be done at present?

  • Play a decent game of table tennis

  • Drive safely along a curving mountain road

  • Drive safely through streets of a closed Air Force base

  • Buy a week's worth of groceries at Berkeley Bowl

  • Play a decent game of bridge

  • Discover and prove a new mathematical theorem

  • Design and execute a research program in molecular biology


State of the art1

State of the art

  • Which of the following can be done at present?

    • Play a decent game of table tennis

    • Drive safely along a curving mountain road

    • Drive safely through streets of a closed Air Force base

    • Buy a week's worth of groceries at Berkeley Bowl (a real grocery store)

    • Play a decent game of bridge

    • Discover and prove a new mathematical theorem

    • Design and execute a research program in molecular biology


Discussion

Discussion

  • To what extend are the following computer systems instances of artificial intelligence

    • Supermarket bar code scanners

    • Web search engines

    • Voice-activated telephone menus

    • Internet routing algorithms that respond dynamically to the state of the network


Discussion1

Discussion

  • “Sure computers cannot be intelligent – they can only do what their programmers tell them.”

    • Is the latter statement true and does it imply the former?


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