344 571 artificial intelligence n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
344-571 ปัญญาประดิษฐ์ ( Artificial Intelligence) PowerPoint Presentation
Download Presentation
344-571 ปัญญาประดิษฐ์ ( Artificial Intelligence)

Loading in 2 Seconds...

play fullscreen
1 / 95

344-571 ปัญญาประดิษฐ์ ( Artificial Intelligence) - PowerPoint PPT Presentation


  • 102 Views
  • Uploaded on

344-571 ปัญญาประดิษฐ์ ( Artificial Intelligence). ดร.วิภาดา เวทย์ประสิทธิ์ ภาควิชาวิทยาการคอมพิวเตอร์ คณะวิทยาศาสตร์ มหาวิทยาลัยสงขลานครินทร์ ห้องทำงาน : CS 320 โทรศัพท์ : 074-288596 E-mail : wwettayaprasit@yahoo.com Website : http://www.cs.psu.ac.th/wiphada. วัตถุประสงค์.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about '344-571 ปัญญาประดิษฐ์ ( Artificial Intelligence)' - leonora


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
344 571 artificial intelligence

344-571 ปัญญาประดิษฐ์(Artificial Intelligence)

ดร.วิภาดา เวทย์ประสิทธิ์

ภาควิชาวิทยาการคอมพิวเตอร์ คณะวิทยาศาสตร์ มหาวิทยาลัยสงขลานครินทร์

ห้องทำงาน : CS 320โทรศัพท์ : 074-288596

E-mail :wwettayaprasit@yahoo.com

Website : http://www.cs.psu.ac.th/wiphada

slide2
วัตถุประสงค์

1. ให้นักศึกษามีความรู้ความเข้าใจเกี่ยวกับปัญญาประดิษฐ์และสาขาต่างๆของปัญญาประดิษฐ์

2. ให้นักศึกษาสามารถพัฒนางานทางด้านปัญญาประดิษฐ์ได้

3. ให้นักศึกษาสามารถค้นคว้าเพิ่มเติมด้วยตนเองได้

วิธีการเรียนการสอน :การบรรยาย การสัมมนา การศึกษาค้นคว้าด้วยตัวเอง

การวัดผล : สอบกลางภาค 35% สอบปลายภาค 40%

สัมมนา 10%Assignment 15%

เวลาเรียน : จันทร์ 1 - 4 ห้อง CS203

ตำรา :Artificial Intelligence second edition, Elaine Rich and Kevin Knight,

McGraw-Hill Inc., 1991.

Chapter 1

slide3

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

Chapter 1

content

Content

  • Artificial IntelligenceArtificial Intelligence FieldsHeuristicTic Tac ToeTuring Test
artificial intelligence
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.

Chapter 1

artificial intelligence1
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.

Chapter 1

artificial intelligence2
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.

Chapter 1

artificial intelligence3
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.

Chapter 1

artificial intelligence4
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.

Chapter 1

artificial intelligence5
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.

Chapter 1

ai areas
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

Chapter 1

task domain of ai
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: Chess

Mathematics : Logic, Geometry

Expert Tasks

Engineering : Design, Fault finding, Manufacturing planning

Scientific analysis

Medical diagnosis

Financial analysis

Chapter 1

robotics
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)

Chapter 1

robotics1
Robotics
  • A legged game from RoboCup 2004 in Lisbon, Portugal
  • Team ENSCO's entry in the first Grand Challenge, DAVID

Chapter 1

robotics2
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.

Chapter 1

robotics3
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.

Chapter 1

robotics4
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.

Chapter 1

robotics5
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.)

Chapter 1

robotics6
Robotics
  • 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.)

Chapter 1

robotics7
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.)

Chapter 1

robotics8
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.

Chapter 1

robotics9
Robotics
  • ASIMO,
  • a humanoid robot manufactured by Honda.

Chapter 1

three laws of robotics
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.

Chapter 1

computer vision1
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.

Chapter 1

computer vision2
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.

Chapter 1

computer vision3
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.

Chapter 1

computer vision4
Computer Vision

Vision based biological species identification systems

Chapter 1

computer vision5
Computer Vision
  • Artist's Concept of Rover on Mars,
  • an example of an unmanned land-based vehicle. Notice the stereo cameras mounted on top of the Rover. (credit: Maas Digital LLC)

Chapter 1

neural network
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

Chapter 1

neural network1
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.

Chapter 1

neural network2
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.

Chapter 1

neural network4
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.

Chapter 1

neural network5
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.

Chapter 1

neural network6
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.

Chapter 1

neural network7
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.

Chapter 1

neural network8
Neural Network
  • Neural networks have been used in pattern recognition, speech analysis, oil exploration, weather prediction, and the modeling of thinking and consciousness.

Chapter 1

machine learning1
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.

Chapter 1

machine learning2
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 learningmethods extract rules and patterns out of massive data sets.

Chapter 1

machine learning3
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.

Chapter 1

machine learning4
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.

Chapter 1

machine learning5
Machine Learning
  • deductive. Logic.
    • The process of reasoning in which a conclusion follows necessarily from the stated premises;inference by reasoningfrom the general to the specific.
    • reasoning from the general to the particular
    • Deduction is the process of drawing conclusions from premises

Chapter 1

machine learning6
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.

Chapter 1

machine learning7
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.

Chapter 1

expert system
Expert System
  • expert systemn.Computer Science.
  • A program that uses available information, heuristics, and inference to suggest solutions to problems in a particular discipline.

Chapter 1

expert system1
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 problem-solving theory. In fact, new principles, tools, and techniques have emerged that form the basis of knowledge engineering.

Chapter 1

expert system2
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.

Chapter 1

expert system3
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.

Chapter 1

expert system4
Expert System

Chapter 1

natural language processing
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 normal-sounding human language, and natural language understanding systems convert samples of human language into more formal representations that are easier for computer programs to manipulate.

Chapter 1

natural language processing1
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

Chapter 1

natural language processing2
Natural Language Processing

Time flies like an arrow

  • A string of words may be interpreted in myriad ways. For example,
    • time moves quickly just like an arrow does;
    • 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.;
    • measure the speed of flying insects like an arrow would - i.e. Time flies in the same way that an arrow would (time them).;
    • measure the speed of flying insects that are like arrows - i.e. Time those flies that are like arrows;
    • a type of flying insect, "time-flies," enjoy arrows (compare Fruit flies like a banana.)

Chapter 1

natural language processing3
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?

Chapter 1

question answering 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.........................................................................

Chapter 1

question answering 2
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:.............................................

Chapter 1

intelligence require knowledge
Intelligence require knowledge
  • 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.

Chapter 1

knowledge representation and search for ai
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.

Chapter 1

common features of ai problems
Common Features of AI Problems
  • The use of computer to do the symbolic reasoning.
  • A focus on problems that do not respond to algorithmic solutions.  Heuristic search.
  • Manipulate the significant quantitative features of a situation rather than relying on numeric methods.
  • Dealing with semantic meaning.
  • Answer that are neither exact nor optimal but “sufficient”.
  • Domain specific knowledge in solving problems.
  • Use meta-level knowledge.

Chapter 1

heuristic
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:

Chapter 1

heuristic1
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.

Chapter 1

heuristic2
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.

Chapter 1

heuristic3
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.

Chapter 1

tic tac toe
tic tac toe

Chapter 1

tic tac toe1
Tic Tac Toe

Chapter 1

homework 1

1 2 3

4 5 6

7 8 9

Homework 1
  • 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.

Tic-Tac-Toe

Chapter 1

tic tac toe program 12

1 2 3

4 5 6

7 8 9

Tic-Tac-Toe : Program 1
  • 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)

Chapter 1

tic tac toe program 22

1 2 3

4 5 6

7 8 9

Tic-Tac-Toe : Program 2

2 = blank

    • 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.

3 =X

5 = O

  • Board : nine element vector representation.

Chapter 1

tic tac toe program 25

8 3 4

1 5 9

6 7 2

Tic-Tac-Toe: Program 2’
  • Board : nine element vector representation.
  • 2 = blank,3 =X,5 = O
    • 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
    • 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.

Chapter 1

tic tac toe program 32

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 :

Chapter 1

the level of the model
The level of the model
  • What is the goal in trying to produce programs that do intelligent things that people do?
  • Are we trying to produce programs that do the tasks the same way people do?
  • Are we attempting to produce programs that simply do the tasks in whatever way appears easiest?

Chapter 1

model human performance
Model human performance
  • To test psychological theories of human performance.

PAPPY {Colby, 1975]

  • To enable computers to understand human reasoning.
  • To enablecomputers to understand computer reasoning.

Chapter 1

turing test
TURING TEST

Columbia Encyclopedia

Alan Mathison Turing

Chapter 1

turing test1
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.

Columbia Encyclopedia

Chapter 1

turing test2
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.

Columbia Encyclopedia

Chapter 1

turing test3
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.

Columbia Encyclopedia

Chapter 1

criteria for success
Criteria for success
  • How will we know if we have succeeded?
  • Turing test. Human ComputerPerson asking?
  • DENDRAL : is a program that analyzes organic compounds to determine their structure.
  • HUMAN CHEMIST COMPUTER

Chapter 1

homework 11
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.

Chapter 1

answers com
Answers.com

Chapter 1

slide95

The End

The road to success is always

under construction

Jim Miller

Chapter 1