cse 471/598 cbs 598 introduction to artificial intelligence

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CSE 471/598 CBS 598 Introduction to Artificial Intelligence Spring 2008 http://www.public.asu.edu/~huanliu/AI08S/ cse471-598.htm

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CSE 471/598 CBS 598 Introduction to Artificial Intelligence. http://www.public.asu.edu/~huanliu/AI08S/cse471-598.htm. Spring 2008. Introduction. You: a future AI Expert TA: Wait to see Time and Place: on the web, Me: Huan Liu, [email protected] ( http://www.public.asu.edu/~huanliu ) - PowerPoint PPT Presentation

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Page 1: CSE 471/598 CBS 598 Introduction to  Artificial Intelligence

CSE 471/598 CBS 598

Introduction to Artificial Intelligence

Spring 2008

http://www.public.asu.edu/~huanliu/AI08S/cse471-598.htm

Page 2: CSE 471/598 CBS 598 Introduction to  Artificial Intelligence

CSE 471/598, CBS 598 H. Liu 2

Introduction

You: a future AI ExpertTA: Wait to seeTime and Place: on the web, Me: Huan Liu, [email protected] (http://www.public.asu.edu/~huanliu) My office hours Slides are updated periodically

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Course introduction

What is AI (many definitions of AI) One definition: a field to enable

computers with human-level intelligence with attempts to understand intelligent entities.

We will evaluate many definitions later.

What is this course about (or why should everyone learn AI?) understand ourselves better build automated intelligent agents improve problem solving skills

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Course workload and evaluation

We will work together - “No pain, no gain!” Projects (30%, 2-3) – all in Lisp or Java? Exam(s) (2*25%) Homework (~20%) Quizzes and class participation (~10% extra)

Which grading system (w/wo +/-) Late penalty, YES and exponentially

increased Academic integrity

(http://www.public.asu.edu/~huanliu/conduct.html)

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Course plan

Text Book: AI - A Modern Approach 2nd Edition in green

Reading assignment: chapters coveredAbout 13-15 chaptersOur goal: “to finish all

these chapters”One major subject per week

TIP Try to keep up and

avoid catch-up

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Major Topics

Intelligent agentsProblem solvingKnowledge and reasoningActing logicallyLearningUncertainty

TIP Comprehend the topics with your common sense

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Welcome to this class!We will work together throughout this semester and your active participation is crucial for the success of the class – the actual shortcut to your success What is a true shortcut?

Questions and suggestions are welcome anytime. E.g., if you find anything incorrect or unclear,

send an email or talk to me, or discuss it in class

You get feedback from us, and I expect feedback from you, too Use myASU to send email and for discussions

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Introduction of AI

- Gearing up for a fun semester about intelligent agents- What is an intelligent agent in your view?

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What is AIAbout thinking and acting

We are not alone, but … (Homo genus) http://en.wikipedia.org/wiki/Homo_(genus)

Acting humanly: The Turing test (by Turing 1950)

Its original purpose What do we need to pass the test?

http://www.loebner.net/Prizef/loebner-prize.html Does that serve our original purpose?

Thinking humanly: Cognitive modeling “Think-aloud” to learn from human and recreate in

computer programs (GPS) What the Eyes see, a camera cannot

http://www.topcharoen.co.th/web/illusion/illusion-a19.gif

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What is AI (2)Thinking rationally: Syllogisms, Logic What would you act on the $50 iBooks incident? Unable to deal with uncertainty Some paradoxes: Liar, Barber

Gödel's incompleteness and Turing's undecidability

Acting rationally: A rational agent (something

that acts) to achieve best or best expected outcomes Some rational actions do not involve inference

An example – a reflex doe not need inference

A set of definitions (Figure 1.1)

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Foundations of AIPhilosophy (428 B.C. - Present) – reasoning and learning Can formal rules be used to draw valid

conclusions? How does the mental mind arise from a

physical brain? Where does knowledge come from? How does knowledge lead to action?

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Mathematics (c. 800 - Present) - logic, probability, decision making, computation What are the formal rules to draw conclusions? What can be computed? How do we reason with uncertain information?

Economics (1776-present) How should we make decisions so as to maximize

payoff? How should we do this when others may not go

along? How should we do this when the payoff may be far

in the future?

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Neuroscience (1861-present) How do brains process information

Processing speed, memory size in a computer (Figure 1.3)

Psychology (1879 - Present) - investigating human mind How do humans and animals think and

act? Mind Wide Open

Computer engineering (1940 - Present) - ever improving tools How can we build an efficient computer?

Moors Law

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Control theory and Cybernetics (1948-present) How can artifacts operate under their

own control? Feedback and adapt

Linguistics (1957 - Present) - the structure and meaning of language How does language relate to thought? Computational linguistics

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Brief History of AIGestation of AI (1943 -1955) McCulloch and Pitts’s model of artificial neurons Minsky’s 40-neuron network Alan Turing’s Computing Machinary and

IntelligenceBirth of AI (1956) A 2-month Dartmouth workshop of 10 attendees –

the name of AI Newell and Simon’s Logic Theorist Should another name like `computational

rationality’ be used? Any suggestion?Early enthusiasm, great expectations (1952 - 1969) GPS by Newell and Simon, Lisp by McCarthy,

Blockworld by Minsky

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AI facing reality (1966 - 1973) Many predictions of AI’s coming successes

A computer would be a chess champion in 10 years (1957)

Machine translation – Syntax is not enough Intractability of the problems attempted by AI “What computers cannot do” in 76

Knowledge-based systems (1969 - 1979) Knowledge is power, acquiring knowledge from

experts Expert systems (MYCIN)

AI - an industry (1980 - present) Many AI systems help companies to save money and

increase productivity

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The return of neural networks (1986 – present) PDP books by Rumelhart and McClelland Connectionist models vs. symbolic models

AI – a science (1987 – present) Build on existing theories vs. propose brand new

ones Rigorous empirical experiments Learn from data – machine learning, data mining

AI – intelligent agents (1995 – present) Working agents embedded in real environments

with continuous sensory inputs

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Some examples of AI applications

Smart bombsDeep Blue, and othersE-Game industry Intelligent housesIntelligent appliances RoboCupMars rovers

BiometricsCommunications (email, word processor)Auto driving from E to W (98% vs. 2%)Consumer protection

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Concluding remarks“The real value of the discipline, Mr. Lazowska said, is less in acquiring a skill with technology tools - the usual definition of computer literacy - than in teaching students to manage complexity; to navigate and assess information; to master modeling and abstraction; and to think analytically in terms of algorithms, or step-by-step procedures.”

from http://www.nytimes.com/2005/08/23/technology/23geeks.html

What is AI about?

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Refresher for LISP

What is it? ANSI Common Lisp, Paul Graham,

Prentice Hall

Input (e.g., terminal, files)Output (e.g., files, printing)Processing (various operations)How to run it?