CSE 471598 CBS 598 Introduction to Artificial Intelligence

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CSE 471/598 CBS 598Introduction to Artificial
Intelligence
http//www.public.asu.edu/huanliu/AI07S/cse471-59
8.htm
Spring 2007
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Introduction

• You Soon-to-be AI Experts
• TA Lei Tang , l.tang_at_asu.edu
• Time and Place on the web,
• Me Huan Liu, hliu_at_asu.edu (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 (multi-purpose)
• understand ourselves better
• build automated intelligent agents
• improve problem solving skills

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Course workload and evaluation

• A lot of work is expected from you. No pain, no
  gain!
• Projects (30, 2-3) all in Lisp?
• Exam(s) (225)
• 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/hua
  nliu/conduct.html)

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Course plan

• Text Book AI - A Modern Approach
• 2nd Edition in green
• Reading assignment chapters covered
• About 13-15 chapters
• Our 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 agents
• Problem solving
• Knowledge and reasoning
• Acting logically
• Learning
• Uncertainty

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 as a whole
• Questions and suggestions are welcome anytime.
• E.g., if you find anything incorrect or unclear,
  send an email or talk to me.
• You get feedback from us, and we expect feedback
  from you, too ?
• Any questions?
• 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 AI

• About 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 AI

• Philosophy (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 AI

• Gestation of AI (1943 -1955)
• McCulloch and Pittss model of artificial neurons
• Minskys 40-neuron network
• Alan Turings Computing Machinary and
  Intelligence
• Birth of AI (1956)
• A 2-month Dartmouth workshop of 10 attendees
  the name of AI
• Newell and Simons 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 AIs 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 bombs
• Deep Blue, and others
• E-Game industry
• Intelligent houses
• Intelligent appliances
• RoboCup
• Mars rovers

• Biometrics
• Communications (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?