Transcript CSE 471/598 Introduction to AI

CSE 471/598,CBS598
Introduction to
Artificial Intelligence
http://www.public.asu.edu/~huanliu/AI04F/cse471-598.htm
Fall 2004
Introduction
You,
TA: Surendra Singhi, Brickyard 214
MW 12:15-1:15, [email protected],
and
me [email protected]
(http://www.public.asu.edu/~huanliu)
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The course
What is AI (many definitions of AI)
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One definition: a field to enable
computers with human-level intelligence
with attempts to understand intelligent
entities.
What is this course about
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understand ourselves better
build automated intelligent agents
improve problem solving skills
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The course (2)
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Projects (30%, 2*15%) – all in Lisp?
Exam(s) (2*25%)
Homework (~20%)
Quizzes and class participation (~10%)
Late penalty, YES.
Academic integrity
(http://www.public.asu.edu/~huanliu/conduct.html)
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Plan
Text Book: AI - A Modern Approach
Reading assignment: chapters covered
15 weeks - about 13-15 chapters
Our goal:
One major subject per week
TIP
Try to keep up and
avoid catch-up
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Plan (2)
Major topics
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Intelligent agents
Problem solving
Knowledge and reasoning
Acting logically
Learning
Uncertainty
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TIP
Comprehend the topics
with your common sense
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Welcome to this class!
We will work together throughout
this semester.
Questions and suggestions are most
welcome.
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Introduction of AI
- Gearing up for a fun semester
about intelligent agents
What is AI (2)
Acting humanly: The Turing test (1950)
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What do we need to pass the test
Thinking humanly: Cognitive modeling
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“Think-aloud” to learn from human and
recreate in computer programs (GPS)
Thinking rationally: Syllogisms, Logic
Acting rationally: A rational agent
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Foundations of AI
Philosophy (428 B.C. - Present) –
reasoning and learning
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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
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What are the formal rules to draw conclusions?
What can be computed?
How do we reason with uncertain information?
Economics (1776-present)
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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)
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How do brains process information
Psychology (1879 - Present) investigating human mind
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How do humans and animals think and act?
Computer engineering (1940 - Present) ever improving tools
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How can we build an efficient computer?
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Control theory and Cybernetics (1948present)
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How can artifacts operate under their own
control?
Linguistics (1957 - Present) - the structure
and meaning of language
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How does language relate to thought?
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Brief History of AI
Gestation of AI (1943 -1955)
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McCulloch and Pitts’s model of artificial neurons
Minsky’s 40-neuron network
Birth of AI (1956)
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A 2-month Dartmouth workshop of 10 attendees –
the name of AI
Newell and Simon’ Logic Theorist
Early enthusiasm, great expectations (1952 1969)
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GPS by Newell and Simon, Lisp by McCarthy, Blockworld
by Minsky
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AI facing reality (1966 - 1973)
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Many predictions of AI coming successes
 A computer would be a chess champion in 10 years (1957)
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Machine translation – Syntax is not enough
Intractability of the problems attempted by AI
Knowledge-based systems (1969 - 1979)
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Knowledge is power, acquiring knowledge from experts
Expert systems (MYCIN)
AI - an industry (1980 - present)
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Many AI systems help companies to save money and
increase productivity
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The return of neural networks (1986 – present)
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PDP books by Rumelhart and McClelland
Connectionist models vs. symbolic models
AI – a science (1987 – present)
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Build on existing theories vs. propose brand new ones
Rigorous empirical experiments
Learn from data – data mining
AI – intelligent agents (1995 – present)
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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
Biometrics
Communications
(email, word
processor)
Auto driving from E to
W (98% vs. 2%)
Consumer protection
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Refresher for LISP
What is it?
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ANSI Common Lisp, Paul Graham, Prentice
Hall
Input (e.g., terminal, files)
Output (e.g., files, printing)
Processing (various operations)
How to run it?
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