Download CE213 Artificial Intelligence – Lecture 1

CE213 Artificial Intelligence – Lecture 1
Module supervisor:
Prof. John Gan, Email: jqgan, Office: 4B.524
Homepage: http://csee.essex.ac.uk/staff/jqgan/
CE213 website: http://orb.essex.ac.uk/ce/ce213/
Learning outcomes, Assessment methods,
Teaching/reading materials, Other resources,
Topics to be covered (http://orb.essex.ac.uk/ce/ce213/ce213%20syllabus.htm)
Timetable (http://orb.essex.ac.uk/ce/ce213/ce213%20timetable.htm)
Acknowledgement:
Some of the lecture notes for this module were
originally prepared by Dr. Paul Scott.
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AI/Robots in sci-fi
2
AI in Reality
Dog or cat? That is the question.
3
Recent News on Artificial Intelligence
Facebook has established an AI Research Lab (https://research.facebook.com/ai/)
Google paid $400m for UK artificial intelligence startup Deep Mind
(http://deepmind.com/) a few years ago.
Google is making driverless cars act more like humans
(http://www.google.com/selfdrivingcar/)
Google’s AlphaGo beats the world champion of Go game
(http://www.bbc.co.uk/news/technology-35810133)
Computer AI passes Turing test in 'world first‘
(http://www.bbc.co.uk/news/technology-27762088)
Artificial intelligence is a very real threat
(http://www.dailymail.co.uk/sciencetech/article-3143275/Artificial-intelligence-real-threat-robots-wipe-humanityACCIDENT-claims-expert.html)
However, no computer program can outperform a little kid in
discriminating cats and dogs. Similar situation is there with robot football.
(http://www.robocup2016.org/ )
What are the grand challenges in AI and robotics?
4
Intelligence
The definition of intelligence is controversial.
Intelligence derives from the Latin verb intelligere, to
comprehend or perceive.
It involves the ability to reason, plan, solve problems,
think abstractly, comprehend complex ideas, learn quickly
and learn from experience, …...
Artificial Intelligence
What is it?
Is it possible?
What use is it?
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What is Artificial Intelligence?
Machines that think. (Turing)
Artificial intelligence is the study of how to make computers do
things which, at the moment, people do better. (Rich & Knight)
Intelligence is concerned mainly with rational action. Artificial
intelligence is thus the study of the problem of building agents
that are intelligent in this sense. (Russell & Norvig)
Artificial intelligence is the study of complex informationprocessing problems that often have their roots in some aspect
of biological information-processing. The goal of the subject is
to identify interesting and solvable information processing
problems, and solve them. (Marr)
…….
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So what is artificial intelligence?
The term “Artificial Intelligence” itself was invented in 1956
(to publicise a conference). The questions that the field
addresses go back much further.
There is no consensus on the meaning of the term.
Two distinct but related themes are apparent:
• Building machines that think and learn like people.
• Building machines that act rationally/intelligently.
7
Is Artificial Intelligence Possible?
Artificial Intelligence and The Philosophy of Mind
For several hundred years people have been arguing about
whether it was possible, in principle, to make a machine that
thinks. (Mainly argued by philosophers at the time when no
computer was available)
The arguments took on a less abstract form about 170 years
ago due to the design of the first general-purpose computer.
It seems that a ‘yes’ answer to this question is obvious now.
However, is there a machine that is genuinely capable of
thinking? (how to test?)
8
Babbage’s Analytical Engine
The first general-purpose computer (it is mechanical!), which
made the AI argument less abstract.
Charles Babbage
Lady Lovelace
Part of Babbage’s Analytical Engine
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The World’s First Programmer
Lady Lovelace and Babbage collaborated on developing the
Analytical Engine.
He designed the hardware
She wrote the programs.
Unfortunately the machine was never finished.
They ran out of money
However Lady Lovelace did develop several key ideas that
have been used by programmers ever since.
e.g., Subroutines
10
The Lady Lovelace’s Objection
In her paper describing the Analytical Engine she said the
following about the possibility that it could “think”:
“The Analytical Engine has no pretensions whatever to
originate anything. It can do whatever we know how to order
it to perform. It can follow analysis, but it has no power of
anticipating any analytical relations or truths.”
In other words:
Computers cannot really think because they can only do what
their programmers tell them to do.
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Rebutting the Objection
In 1950, Alan Turing published a paper “Computing Machine
and Intelligence”, addressing a range of objections to the idea
that computers could think. (http://www.csee.umbc.edu/courses/471/papers/turing.pdf)
One of these was Lady Lovelace’s Objection.
Turing had two counterarguments:
• In practice, the results of programming often surprise us.
(Lady Lovelace never got to run any of her programs!)
• The possibility that machines could be programmed to
learn.
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The Turing Test
Turing proposed a test which could be used to determine if a machine
was capable of thinking like a person.
It is derived from something he calls the imitation game, which was
apparently played at parties.
• It requires three people: a man A, a woman B, and an interrogator
C.
• C is in a different room from A and B. Communication is only by
typewritten notes.
• C sends questions to A and B. His objective is to determine on the
basis of their replies which one is the woman.
• A’s objective is to lead C to the wrong answer; B’s objective is to
help C to the right answer.
(Obviously Turing went to some very dull parties!)
13
The Turing Test (2)
Turing’s variant of the game replaces either
A or B with a computer and communication
with teletype links. The objective is for C to
guess which one is the computer.
Turing argues that if a computer were
capable of successfully playing this game
then we would have to concede it was as
capable of thought as a human being. This
is essentially a behavioural argument - If an
entity behaves as if it thinks then it thinks.
Should more interrogators be involved in Turing Test to make it
more reliable? Even if so, is Turing Test valid for evaluating AI?
Is Turing Test itself a refutation of Lady Lovelace’s Objection?
14
Searle’s Chinese Room
(https://en.wikipedia.org/wiki/John_Searle)
Strong AI and Weak AI
Consider the following two definitions of artificial intelligence:
A machine that thinks like a person.
A machine that acts as if it thinks like a person.
To some people, the distinction between these two is
unimportant.
For example, Turing’s central claim is essentially that if a
machine acts as if it thinks then we should conclude that it
does think.
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Searle’s Chinese Room (2)
Searle has strongly criticised this view. He distinguishes
Weak AI: The attempt to build machines that act as if they
think.
Strong AI: The attempt to build machines that think.
He has no quarrel with weak AI, which he regards as essentially
a technological undertaking.
He profoundly disagrees with the view that Weak AI and Strong
AI are equivalent.
Furthermore, he does not believe Strong AI is possible.
16
Searle’s Chinese Room (3)
The Chinese Room
In order to demonstrate the difference between weak and strong
AI, Searle developed an analogy known as the “Chinese Room”.
The following is a minor variation.
Imagine an English speaking person locked in a room, who
has no knowledge of Chinese or Russian.
Periodically this person is given texts written in Chinese.
Also in the room is a (large) set of rules, written in English, for
manipulating the symbols of Chinese text and producing
Russian translations.
By mechanically following these rules, the person produces
Russian translations of the Chinese text.
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Searle’s Chinese Room (4)
Searle argues:
The room+person system behaves as if it understands Chinese.
It is obvious that no understanding is involved.
Hence behaviour does not imply the existence of a mind that
understands.
In other words, weak AI does not imply strong AI.
Thus, if you accept Searle’s argument, then Turing test is not a valid
method for assessing whether a machine can think.
What would be a better way to test whether (strong) AI is possible?
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What Use is Artificial Intelligence?
In 1973, a report commissioned by the UK Research Councils
concluded that AI was only worth extremely limited funding.
Would a similar report in 2016 reach similar conclusions?
Artificial Intelligence Research – EPSRC Funding
(https://www.epsrc.ac.uk/research/ourportfolio/researchareas/ait/)
19
AI as Technology
AI research provides powerful problem solving tools.
Since 1980 AI has established itself as a powerful tool that
organisations use to automate their business processes.
AI exports its successes
Expert systems
Data mining
Machine vision
Speech and natural language understanding
Search techniques
Game playing
Robots for personal services
……..
20
AI as Science
AI is important scientifically in two respects:
As a discipline in its own right:
Here the fundamental questions concern how it is possible to create
intelligent systems that perform challenging tasks.
As a tool for the cognitive sciences:
i.e., psychology, linguistics, anthropology, sociology, philosophy .
In the past these disciplines have suffered in comparison to the physical
sciences because they lacked a counterpart to mathematics in which
theories could be precisely formulated and their consequences
determined.
AI provides both a vehicle for the formulation of such theories and a set
of concepts that can be used to create new theories.
e.g., intelligent data mining for neuroscience.
L. Zhang, J.Q. Gan, and H. Wang, “Mathematically gifted adolescents mobilize enhanced workspace
configuration of theta cortical network during deductive reasoning,” Neuroscience, vol. 289, pp. 334349, 2015.
21
Summary
What is Artificial Intelligence?
Building machines that think and learn like people.
Building machines that act rationally/intelligently.
Is Artificial Intelligence Possible?
Lady Lovelace’s Objection
The Turing Test
Searle’s Chinese Room
What Use is Artificial Intelligence?
Artificial Intelligence as Technology
Artificial Intelligence as Science
or
Have you got the
answers to these
questions now?
What are you going
to learn next?
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An Example of AI via Machine Learning
Neural network model:
nh
yk = f ( ∑ wkio ⋅ hi − θ ko )
i =1
nh
n
= f ( ∑ w ⋅ f ( ∑ wijh ⋅ x j − θih ) − θ ko )
o
ki
Happy
i =1
j =1
Learning algorithm:
∆w = α ( z − y )
e=
dy
de
= −α
dw
dw
1
( z − y )2
2
Error reduction by learning:
e(w)
(preprocessing & feature extraction)
…
…
…
local minimum
Positive
w1
(partly from www.kdnuggets.com)
(
de
< 0, ∆ w > 0 )
dw
w
w* w2
(
de
> 0, ∆ w < 0 )
dw
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