344-571
ปัญญาประดิษฐ์
(Artificial Intelligence)
ผศ.ดร.วิภาดา เวทย์ประสิ ทธิ์
ภาควิชาวิทยาการคอมพิวเตอร์ คณะวิทยาศาสตร์ มหาวิทยาลัยสงขลานคริ นทร์
ห้องทางาน : CS 108 โทรศัพท์ : 074-288580
E-mail : [email protected]
Website : http://www.cs.psu.ac.th/wiphada
วัตถุประสงค์
1. ให้นกั ศึกษามีความรู้ความเข้าใจเกี่ยวกับปัญญาประดิษฐ์และสาขาต่างๆของปัญญาประดิษฐ์
2. ให้นกั ศึกษาสามารถพัฒนางานทางด้านปัญญาประดิษฐ์ได้
3. ให้นกั ศึกษาสามารถค้นคว้าเพิ่มเติมด้วยตนเองได้
วิธีการเรี ยนการสอน : การบรรยาย การสัมมนา การศึกษาค้นคว้าด้วยตัวเอง
การวัดผล : สอบกลางภาค 30%
สอบปลายภาค 40%
LAB & Assignment
ตารา :
30%
Artificial Intelligence second edition, Elaine Rich and Kevin Knight,
McGraw-Hill Inc.,
Artificial Intelligence
1991.
2
Chapter 1
เนื้อหาวิชา
Chapter 1 : What is Artificial Intelligence?
Chapter 2 : Problems and Spaces
Chapter 3 : Heuristic Search
Chapter 4 : Natural Language Processing
Chapter 5 : Machine Learning
Chapter 6 : Robotics
Chapter 7 : Neural Networks
Chapter 8 : Expert Systems
Chapter 9 : Computer Vision
Artificial Intelligence
3
Chapter 1
Chapter 1
What is Artificial Intelligence?
Content
•
Artificial Intelligence
Artificial Intelligence Fields
Heuristic
Tic Tac Toe
Turing Test
Artificial Intelligence
artificial intelligence
n. (Abbr. AI)
The ability of a computer or other machine to
perform those activities that are normally
thought to require intelligence.
The branch of computer science concerned with
the development of machines having this
ability.
Artificial Intelligence
6
Chapter 1
Artificial Intelligence
• The subfield of computer science concerned
with understanding the nature of intelligence
and constructing computer systems capable
of intelligent action.
• It embodies the dual motives of furthering
basic scientific understanding and making
computers more sophisticated in the service
of humanity.
Artificial Intelligence
7
Chapter 1
Artificial Intelligence
• Many activities involve intelligent action
—problem solving, perception, learning,
planning and other symbolic reasoning,
creativity, language, and so forth—and
therein lie an immense diversity of
phenomena.
Artificial Intelligence
8
Chapter 1
Artificial Intelligence
• Computer Encyclopedia
• (Artificial Intelligence) Devices and
applications that exhibit human intelligence
and behavior including robots, expert
systems, voice recognition, natural and
foreign language processing.
It also implies the ability to learn and adapt
through experience.
Artificial Intelligence
9
Chapter 1
Artificial Intelligence
Wikipedia
The term Artificial Intelligence (AI) was
first used by John McCarthy who
considers it to mean "the science and
engineering of making intelligent
machines".[1]
It can also refer to intelligence as
exhibited by an artificial (man-made,
non-natural, manufactured) entity.
Artificial Intelligence
10
Chapter 1
Artificial Intelligence
Wikipedia
AI is studied in overlapping fields of
computer science, psychology,
neuroscience and engineering,
dealing with intelligent behavior,
learning and adaptation and usually
developed using customized
machines or computers.
Artificial Intelligence
11
Chapter 1
History of Artificial Intelligence
1950
1951
1956
1958
Alan Turing introduces the Turing test intended to test a machine's capability to
participate in human-like conversation.
The first working AI programs were written to run on the Ferranti Mark I machine
of the University of Manchester: a checkers-playing program written by
Christopher Strachey and a chess-playing program written by Dietrich Prinz.
John McCarthy coined the term "artificial intelligence" as the topic of the
Dartmouth Conference.
John McCarthy invented the Lisp programming language.
Joseph Weizenbaum built ELIZA, an interactive program that carries on a dialogue
1965 in English language on any topic.
Edward Feigenbaum initiated DENDRAL, a 10-yr effort to develop software to
deduce the molecular structure of organic compounds using scientific instrument
1965 data. It was the first expert system.
Artificial Intelligence
12
Chapter 1
History of Artificial Intelligence
1966
1968
1972
1973
1974
1997
1999
2004
Machine Intelligence workshop at Edinburgh - the first of an influential annual series
organized by Donald Michie and others.
HAL 9000 made its appearance in the science fiction movie 2001: A Space Odyssey.
The Prolog programming language was developed by Alain Colmerauer.
Edinburgh Freddy Assembly Robot: a versatile computer-controlled assembly system.
Ted Shortliffe's PhD dissertation on the MYCIN program (Stanford) demonstrated a very
practical rule-based approach to medical diagnoses, even in the presence of uncertainty.
While it borrowed from DENDRAL, its own contributions strongly influenced the future of
expert system development, especially commercial systems.
The Deep Blue chess program (IBM) beats the world chess champion, Garry Kasparov.
Sony introduces the AIBO, an artificially intelligent pet.
DARPA introduces the DARPA Grand Challenge requiring competitors to produce
autonomous vehicles for prize money.
Artificial Intelligence
13
Chapter 1
Artificial Intelligence
Typical problems to which AI methods are applied
Pattern recognition
Computer vision, Virtual reality and Image processing
Optical character recognition Diagnosis (artificial intelligence)
Handwriting recognition
Game theory and Strategic planning
Speech recognition
Game artificial intelligence and Computer game bot
Face recognition
Natural language processing, Translation and Chatterbots
Artificial Creativity
Non-linear control and Robotics
Artificial Intelligence
14
Chapter 1
AI Areas
•Artificial Intelligence (AI) :
•the branch o f computer science that is concerned with the
automation of intelligent behavior.
•AI Areas :
• Game Playing
• Automated Reasoning and Theorem Proving
• Expert Systems
• Natural Language Understanding and Semantics Modeling
• Modeling Human Performance
• Planning and Robotics
• Machine Leaning
• Neural Networks
Artificial Intelligence
15
Chapter 1
Task Domain of AI
Mundane Tasks
mundane(มันเดน) adj. ทางโลก
Perception : Vision, Speech
Natural language : Understanding, Generation, Translation
Commonsense reasoning
Robot control
Formal Tasks
Games:
Mathematics :
Chess
Logic, Geometry
Expert Tasks
Engineering :
Design, Fault finding, Manufacturing planning
Scientific analysis
Medical diagnosis
Financial analysis
Artificial Intelligence
16
Chapter 1
Artificial Intelligence Fields
Robotics
• Shakey the Robot
Developed in 1969 by the
Stanford Research
Institute, Shakey was the
first fully mobile robot with
artificial intelligence. Seven
feet tall, Shakey was
named after its rather
unstable movements.
(Image courtesy of The
Computer History Museum,
www.computerhistory.org)
Artificial Intelligence
18
Chapter 1
Robotics
• A legged game
from RoboCup
2004 in Lisbon,
Portugal
• Team ENSCO's entry in
the first Grand
Challenge, DAVID
Artificial Intelligence
19
Chapter 1
Robotics
• The DARPA Grand Challenge is
a race for a $2 million prize
where cars drive themselves
across several hundred miles of
challenging desert terrain
without any communication
with humans, using GPS,
computers and a sophisticated
array of sensors. In 2005 the
winning vehicles completed all
132 miles of the course in just
under 7 hours.
Artificial Intelligence
20
Chapter 1
Robotics
• ro·bot
A mechanical device that sometimes
resembles a human and is capable of
performing a variety of often complex human
tasks on command or by being programmed in
advance.
• A machine or device that operates
automatically or by remote control.
• A person who works mechanically without
original thought, especially one who responds
automatically to the commands of others.
Artificial Intelligence
21
Chapter 1
Robotics
• Computer Encyclopedia
• robot
• A stand-alone hybrid computer system that
performs physical and computational activities.
Capable of performing many different tasks, it
is a multiple-motion device with one or more
arms and joints.
• Robots can be similar in form to a human, but
industrial robots do not resemble people at all.
Artificial Intelligence
22
Chapter 1
Robotics
• Huey, Dewey and Louie
• Named after Donald
Duck's famous nephews,
robots at this Wayne,
Michigan plant apply
sealant to prevent possible
water leakage into the car.
Huey (top) seals the drip
rails while Dewey (right)
seals the interior weld
seams. Louie is outside of
the view of this picture.
(Image courtesy of Ford
Motor Company.)
Artificial Intelligence
23
Chapter 1
Robotics
Artificial Intelligence
• Inspect Pipes from the
Inside
• Developed by SRI for
Osaka Gas in Japan, this
Magnetically Attached
General Purpose
Inspection Engine
(MAGPIE) goes inside gas
pipes and looks for leaks.
This unit served as the
prototype for multicar
models that perform
temporary repairs while
capturing pictures. (Image
courtesy of SRI
International.)
24
Chapter 1
Robotics
• Computers Making
Computers
• Robots, whose brains
are nothing but chips,
are making chips in
this TI fabrication
plant. (Image courtesy
of Texas Instruments,
Inc.)
Artificial Intelligence
25
Chapter 1
Robotics
• How Small Can They
Get?
• By 2020, scientists at
Rutgers University believe
that nano-sized robots will
be injected into the
bloodstream and administer
a drug directly to an infected
cell. This robot has a carbon
nanotube body, a
biomolecular motor that
propels it and peptide limbs
to orient itself.
Artificial Intelligence
26
Chapter 1
Robotics
• ASIMO,
• a humanoid robot
manufactured by
Honda.
Artificial Intelligence
27
Chapter 1
Three Laws of Robotics
•
•
•
A robot may not injure a human being or,
through inaction, allow a human being to
come to harm.
A robot must obey orders given it by human
beings except where such orders would
conflict with the First Law.
A robot must protect its own existence as
long as such protection does not conflict with
the First or Second Law.
Artificial Intelligence
28
Chapter 1
Computer Vision
Artificial Intelligence
29
Chapter 1
Computer Vision
• Computer vision
• The technology concerned with
computational understanding and use of
the information present in visual images.
• In part, computer vision is analogous
(similar) to the transformation of visual
sensation into visual perception in
biological vision.
Artificial Intelligence
30
Chapter 1
Computer Vision
• For this reason the motivation, objectives,
formulation, and methodology of computer
vision frequently intersect with knowledge
about their counterparts in biological vision.
However, the goal of computer vision is
primarily to enable engineering systems to
model and manipulate the environment by
using visual sensing.
Artificial Intelligence
31
Chapter 1
Computer Vision
• Field of robotics in which programs
attempt to identify objects represented
in digitized images provided by video
cameras, thus enabling robots to "see."
• Much work has been done on stereo
vision as an aid to object identification
and location within a three-dimensional
field of view. Recognition of objects in
real time.
Artificial Intelligence
32
Chapter 1
Computer Vision
Vision based biological
species identification
systems
Artificial Intelligence
33
Chapter 1
Computer Vision
• Artist's Concept of
Rover on Mars,
• an example of an
unmanned landbased vehicle.
Notice the stereo
cameras mounted
on top of the
Rover. (credit:
Maas Digital LLC)
Artificial Intelligence
34
Chapter 1
Neural Network
• neural network also neural net n.
• A real or virtual device, modeled after
the human brain, in which several
interconnected elements process
information simultaneously, adapting
and learning from past patterns
Artificial Intelligence
35
Chapter 1
Neural Network
• Computer Encyclopedia
• neural network
• A modeling technique based on
the observed behavior of
biological neurons and used to
mimic (imitate) the performance
of a system.
Artificial Intelligence
36
Chapter 1
Neural Network
• It consists of a set of elements that start
out connected in a random pattern, and,
based upon operational feedback, are
molded into the pattern required to
generate the required results.
• It is used in applications such as
robotics, diagnosing, forecasting, image
processing and pattern recognition.
Artificial Intelligence
37
Chapter 1
Neural Network
Artificial Intelligence
38
Chapter 1
Machine Learning
Artificial Intelligence
39
Chapter 1
Neural Network
• Accounting Dictionary
• Neural Networks
• Technology in which computers actually
try to learn from the data base and
operator what the right answer is to a
question.
Artificial Intelligence
40
Chapter 1
Neural Network
• The system gets positive or negative response
to output from the operator and stores that
data so that it will make a better decision the
next time.
• While still in its infancy, this technology shows
promise for use in accounting, fraud detection,
economic forecasting, and risk appraisals.
• The idea behind this software is to convert the
order-taking computer into a "thinking"
problem solver.
Artificial Intelligence
41
Chapter 1
Neural Network
• Britannica Concise Encyclopedia
• neural network
• Type of parallel computation in which
computing elements are modeled on the
network of neurons that constitute animal
nervous systems.
• This model, intended to simulate the way the
brain processes information, enables the
computer to "learn" to a certain degree.
Artificial Intelligence
42
Chapter 1
Neural Network
• A neural network typically consists of a
number of interconnected processors, or
nodes. Each handles a designated sphere
of knowledge, and has several inputs and
one output to the network. Based on the
inputs it gets, a node can "learn" about
the relationships between sets of data,
sometimes using the principles of fuzzy
logic.
Artificial Intelligence
43
Chapter 1
Neural Network
• Neural networks have been used
in pattern recognition, speech
analysis, oil exploration, weather
prediction, and the modeling of
thinking and consciousness.
Artificial Intelligence
44
Chapter 1
Machine Learning
• Sci-Tech Dictionary
• machine learning (mə′shēn ′lərn·iŋ)
• (computer science) The process or
technique by which a device modifies
its own behavior as the result of its
past experience and performance.
Artificial Intelligence
45
Chapter 1
Machine Learning
• Wikipedia
• machine learning is concerned with the
development of algorithms and
techniques that allow computers to
"learn".
• At a general level, there are two types of
learning: inductive, and deductive.
Inductive machine learning methods
extract rules and patterns out of massive
data sets.
Artificial Intelligence
46
Chapter 1
Machine Learning
• inductive,
• Logic.
– The process of deriving general principles from
particular facts or instances.
• Mathematics.
– A two-part method of proving a theorem involving an
integral parameter. First the theorem is verified for
the smallest admissible value of the integer. Then it
is proven that if the theorem is true for any value of
the integer, it is true for the next greater value. The
final proof contains the two parts.
Artificial Intelligence
47
Chapter 1
Machine Learning
• inductive,
• reasoning from detailed facts to general
principles
– Rule induction is an area of machine
learning in which formal rules are extracted
from a set of observations.
Artificial Intelligence
48
Chapter 1
Machine Learning
• deductive. Logic.
– The process of reasoning in which a
conclusion follows necessarily from the
stated premises; inference by reasoning from
the general to the specific.
– reasoning from the general to the particular
– Deduction is the process of drawing
conclusions from premises
Artificial Intelligence
49
Chapter 1
Machine Learning
– Deduction The process of reaching a
conclusion through reasoning from general
premises to a specific premise.
– An example of deduction is present in the
following syllogism:
– Premise: All mammals are animals.
– Premise: All whales are mammals.
– Conclusion: Therefore, all whales are
animals.
Artificial Intelligence
50
Chapter 1
Machine Learning
• deduction, in logic, form of inference such
that the conclusion must be true if the
premises are true.
• For example,
– if we know that….. all men have two legs
– And that …………..John is a man,
– it is then logical to deduce that
……………………..John has two legs.
Artificial Intelligence
51
Chapter 1
Expert System
• expert system
n. Computer Science.
• A program that uses available
information, heuristics, and
inference to suggest solutions to
problems in a particular
discipline.
Artificial Intelligence
52
Chapter 1
Expert System
• Expert systems
• Methods and techniques for constructing
human-machine systems with specialized
problem-solving expertise.
• The pursuit of this area of artificial intelligence
research has emphasized the knowledge that
underlies human expertise and has
simultaneously decreased the apparent
significance of domain-independent problemsolving theory. In fact, new principles, tools,
and techniques have emerged that form the
basis of knowledge engineering.
Artificial Intelligence
53
Chapter 1
Expert System
• Expertise consists of knowledge about a
particular domain, understanding of domain
problems, and skill at solving some of these
problems.
• Knowledge in any specialty is of two types,
public and private.
• Public knowledge includes the published
definitions, facts, and theories which are
contained in textbooks and references in
the domain of study. But expertise usually
requires more than just public knowledge.
Artificial Intelligence
54
Chapter 1
Expert System
• Human experts generally possess private
knowledge which has not found its way
into the published literature.
• This private knowledge consists largely of
rules of thumb or heuristics.
• Heuristics enable the human expert to
make educated guesses when necessary,
to recognize promising approaches to
problems, and to deal effectively with
erroneous or incomplete data.
Artificial Intelligence
55
Chapter 1
Expert System
Category
Problem addressed
Interpretations
Inferring situation descriptions from sensor data
Prediction
Inferring likely consequences of given situations
Diagnosis
Inferring system malfunctions from observables
Design
Configuring objects under constraints
Planning
Designing actions
Monitoring
Comparing observations to plan vulnerabilities
Debugging
Prescribing remedies for malfunctions
Repair
Executing a plan to administer a prescribed
remedy
Instruction
Diagnosing, debugging, and repairing students'
knowledge
Artificial Intelligence
56
Chapter 1
Natural Language Processing
• Wikipedia
• Natural language processing (NLP) is a
subfield of artificial intelligence and linguistics.
It studies the problems of automated
generation and understanding of natural human
languages.
• Natural language generation systems convert
information from computer databases into normalsounding human language, and natural language
understanding systems convert samples of human
language into more formal representations that are
easier for computer programs to manipulate.
Artificial Intelligence
57
Chapter 1
Natural Language Processing
• We gave the monkeys the bananas because
they were hungry and We gave the monkeys
the bananas because they were over-ripe.
• have the same surface grammatical structure.
However, in one of them the word they refers
to the monkeys, in the other it refers to the
bananas:
• the sentence cannot be understood properly
without knowledge of the properties and
behaviour of monkeys
Artificial Intelligence
58
Chapter 1
Natural Language Processing
Time flies like an arrow
•
A string of words may be interpreted in myriad ways. For example,
1. time moves quickly just like an arrow does;
2. measure the speed of flying insects like you would
measure that of an arrow - i.e. (You should) time flies
like you would an arrow.;
3. measure the speed of flying insects like an arrow
would - i.e. Time flies in the same way that an arrow
would (time them).;
4. measure the speed of flying insects that are like
arrows - i.e. Time those flies that are like arrows;
5. a type of flying insect, "time-flies," enjoy arrows
(compare Fruit flies like a banana.)
Artificial Intelligence
59
Chapter 1
Natural Language Processing
•"pretty little girls' school"
• English and several other languages don't specify
which word an adjective applies to.
• For example, in the string "pretty little girls'
school".
– Does the school look little?
– Do the girls look little?
– Do the girls look pretty?
– Does the school look pretty?
Artificial Intelligence
60
Chapter 1
Question Answering 1
•
Russia massed troops on the Czech border.
• POLITICS program [Corbonell,1980)
Q1: Why did Russia do this?
A1:......................................................................
Q1: What should the United States do?
A2: .....................................................................
OR
A2........................................................................
.
Artificial Intelligence
61
Chapter 1
Question Answering 2
•Mary went shopping for a new coat.
•She found a red one she really liked.
•When she got it home, she discovered that it went perfectly
with her favorite dress.
ELIZA
Q1:What did Mary go shopping for?
A1: .............................................
Q2:What did Mary find she liked?
A2:.............................................
Q3: Did Mary buy anything ?
A3:.............................................
Artificial Intelligence
62
Chapter 1
Intelligence require knowledge
1.
2.
3.
4.
It is voluminous.
It is hard to characterize accurately.
It is constantly changing.
It differs from data by being
organized in a way that corresponds
to the ways it will be used.
Artificial Intelligence
63
Chapter 1
Knowledge Representation and Search for AI
 The knowledge captures generalizations.
 It can be understood by people who must
provide it.
 It can easily be modified to correct errors
and to reflect changes in the world.
 It can be used in many situations even if
it is not totally accurate or complete.
 It can use to narrow the range of
possibilities that must usually be
considered.
Artificial Intelligence
64
Chapter 1
Common Features of AI Problems
1. The use of computer to do the symbolic reasoning.
2. A focus on problems that do not respond to
algorithmic solutions.  Heuristic search.
3. Manipulate the significant quantitative features of a
situation rather than relying on numeric methods.
4. Dealing with semantic meaning.
5. Answer that are neither exact nor optimal but
“sufficient”.
6. Domain specific knowledge in solving problems.
7. Use meta-level knowledge.
Artificial Intelligence
65
Chapter 1
Heuristic
• heu·ris·tic (hyʊ-rĭs'tĭk)
adj.
• Of or relating to a usually
speculative formulation serving
as a guide in the investigation or
solution of a problem:
Artificial Intelligence
66
Chapter 1
Heuristic
• Of or constituting an educational method in
which learning takes place through discoveries
that result from investigations made by the
student.
• Computer Science. Relating to or using a
problem-solving technique in which the most
appropriate solution of several found by
alternative methods is selected at successive
stages of a program for use in the next step of
the program.
Artificial Intelligence
67
Chapter 1
Heuristic
• Computer Encyclopedia
• heuristic
• A method of problem solving using
exploration and trial and error methods.
Heuristic program design provides a
framework for solving the problem in
contrast with a fixed set of rules
(algorithmic) that cannot vary.
Artificial Intelligence
68
Chapter 1
Heuristic
• Business Dictionary
• Heuristic
• Method of solving problems that
involves intelligent trial and error,
such as playing chess. By contrast,
an algorithmic solution method is a
clearly specified procedure that is
guaranteed to give the correct
answer.
Artificial Intelligence
69
Chapter 1
tic tac toe
Artificial Intelligence
70
Chapter 1
Tic Tac Toe
Artificial Intelligence
71
Chapter 1
3D Tic Tac Toe
Artificial Intelligence
72
Chapter 1
Homework 1
Tic-Tac-Toe
1
2
3
4
5
6
7
8
9
• Read program 1, 2 and 3 and discuss
the following criteria.
 Their Complexity
 Their use of generalization.
 The clarity of their knowledge.
 The extensibility of their approach.
Artificial Intelligence
73
Chapter 1
Tic-Tac-Toe : Program 1
Artificial Intelligence
74
Chapter 1
Tic-Tac-Toe : Program 1
Artificial Intelligence
75
Chapter 1
Tic-Tac-Toe : Program 1
1
2
3
4
5
6
7
8
9
• Board : nine element vector representation.
• 0 = blank,
1 =X,
2=O
• Moveable : Their Complexity = 39 = 19,683
– view vector board as a ternary number (base three)
Artificial Intelligence
76
Chapter 1
Tic-Tac-Toe : Program 2
Artificial Intelligence
77
Chapter 1
Tic-Tac-Toe : Program 2
Artificial Intelligence
78
Chapter 1
Tic-Tac-Toe : Program 2
1
2
3
2 = blank
4
5
6
3 =X
7
8
9
5=O
•Board : nine element vector representation.
– an integer indicating which move of the game is about to played.
– 1 indicate the first move.
– 9 indicate the last move.
– Board[5] = 2  mean blank
•
Poswin(p) : If it produce (3*3*2) =18  X can win
– p = 0 if the player can not win on his next move.
•
•
Poswin(p) : If it produce (5*5*2) =50 O can win
Go(n) : Make a move on square n.
– TURN is odd  if it is playing X
– TURN is even  if it is playing O
– More efficient in term of space.
Artificial Intelligence
79
Chapter 1
Tic-Tac-Toe : Program 2’
Artificial Intelligence
80
Chapter 1
Tic-Tac-Toe : Program 2’
Artificial Intelligence
81
Chapter 1
Tic-Tac-Toe : Program 2’
•
•
4
1
5
9
6
7
2
an integer indicating which move of the game is about to played.
1 indicate the first move.
9 indicate the last move.
Board[5] = 2  mean blank
Poswin(p) : If it produce MAGIC SQUARE
– (8 + 3 + 4) =15
–
•
3
Board : nine element vector representation.
2 = blank,
3 =X,
5=O
–
–
–
–
•
8
p = 0 if the player can not win on his next move.
Go(n) : Make a move on square n.
– TURN is odd  if it is playing X
– TURN is even  if it is playing O
– More efficient in term of space.
Artificial Intelligence
82
Chapter 1
Tic-Tac-Toe : Program 3
Artificial Intelligence
83
Chapter 1
Tic-Tac-Toe : Program 3
Artificial Intelligence
84
Chapter 1
1
2
3
4
5
6
7
8
9
•
•
Tic-Tac-Toe : Program 3
Board_Position : nine element vector representing the board, a list
of board positions that could result from the next move, and a
number representing as estimate of how likely the board position is
lead to an ultimate win for the player to move.
Minimax Procedure : in chapter 12.
– We maximize the likely hood of winning the game,
– While opponent Minimize the likely hood of winning the game
•
Decide which of a set of board positions is best.
– find highest possible rating.
– consider all the moves the component could make next.
–  See which move is worst for us....
(Assume the opponent will make that move)
•
•
•
Look forward many steps in advance.
Search tree : need more time
Use AI technique :
Artificial Intelligence
85
Chapter 1
The level of the model
1. What is the goal in trying to
produce programs that do
intelligent things that people do?
2. Are we trying to produce programs
that do the tasks the same way
people do?
3. Are we attempting to produce
programs that simply do the tasks
in whatever way appears easiest?
Artificial Intelligence
86
Chapter 1
Model human performance
1. To test psychological theories of
human performance.
PAPPY {Colby, 1975]
2. To enable computers to
understand human reasoning.
3. To enable computers to
understand computer reasoning.
Artificial Intelligence
87
Chapter 1
TURING TEST
Alan Mathison Turing
Artificial Intelligence
88
Chapter 1
TURING TEST
• Columbia Encyclopedia
• Turing test, a procedure to test whether
a computer is capable of humanlike
thought. As proposed (1950) by the
British mathematician Alan Turing, a
person (the interrogator) sits with a
teletype machine isolated from two
correspondents—one is another person,
one is a computer.
Artificial Intelligence
89
Chapter 1
TURING TEST
• By asking questions through the
teletype and studying the
responses, the interrogator tries
to determine which correspondent
is human and which is the
computer.
Artificial Intelligence
90
Chapter 1
TURING TEST
• The computer is programmed to give
deceptive answers, e.g., when asked to add
two numbers together, the computer pauses
slightly before giving the incorrect sum
—to imitate what a human might do,
the computer gives an incorrect answer
slowly since the interrogator would expect
the machine to give the correct answer
quickly.
• If it proves impossible for the interrogator to
discriminate between the human and the
computer, the computer is credited with
having passed the test.
Artificial Intelligence
91
Chapter 1
Criteria for success
•
How will we know if we have succeeded?
•
Turing test. Human
•
DENDRAL : is a program that analyzes organic
compounds to determine their structure.
•
HUMAN CHEMIST
Artificial Intelligence
Computer
Person asking?
COMPUTER
92
Chapter 1
Homework 1
1. Given the meaning of Artificial Intelligence from
your point of view. You may add citation from
searching documents in the web or from the text
book.
2. Given all AI fields with some explanations.
Artificial Intelligence
93
Chapter 1
Answers.com
Artificial Intelligence
94
Chapter 1
Jim Miller
Artificial Intelligence
95
Chapter 1
Descargar

323-670 ปัญญาประดิษฐ์ (Artificial Intelligence)