450 101 Management Information System Artificial Intelligence Expert

450 -101 Management Information System Artificial Intelligence & Expert Systems ��. ���������� Office : CS 320, Computer Science Building Email : wwettayaprasit@yahoo. com Website : http: //staff. cs. psu. ac. th/wiphada Phone : 0 -7428 -8596

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. 323 -670 Artificial Intelligence 2 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. 323 -670 Artificial Intelligence 3 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. 323 -670 Artificial Intelligence 4 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. 323 -670 Artificial Intelligence 5 Chapter 1

Artificial Intelligence Wikipedia The term Artificial Intelligence (AI) was first used by John Mc. Carthy 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. 323 -670 Artificial Intelligence 6 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. 323 -670 Artificial Intelligence 7 Chapter 1

tic tac toe 323 -670 Artificial Intelligence 8 Chapter 1

Tic Tac Toe 323 -670 Artificial Intelligence 9 Chapter 1

3 D Tic Tac Toe 323 -670 Artificial Intelligence 10 Chapter 1

Artificial Intelligence Fields 1. Natural Language Processing Neural Networks Machine Learning Robotics Computer Vision Expert Systems

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. 323 -670 Artificial Intelligence 12 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 323 -670 Artificial Intelligence 13 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. ) 323 -670 Artificial Intelligence 14 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 pretty? – Does the school look pretty? 323 -670 Artificial Intelligence 15 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 Q 1: What did Mary go shopping for? A 1: . . . Q 2: What did Mary find she liked? A 2: . . . Q 3: Did Mary buy anything ? A 3: . . . 323 -670 Artificial Intelligence 16 Chapter 1

S NP John VP V saw NP PP PP with a telescope DET N the boy in the park John saw the boy in the park with a telescope. Figure 14. 5: More Interaction among Components 323 -670 Artificial Intelligence 17 Chapter 1

S NP John VP V saw NP DET N PP the boy PP in the park with a dog John saw the boy in the park with a dog. Figure 14. 5: More Interaction among Components 323 -670 Artificial Intelligence 18 Chapter 1

S NP John VP NP V saw DET N the boy PP in the park with a statue John saw the boy in the park with a statue. Figure 14. 5: More Interaction among Components 323 -670 Artificial Intelligence 19 Chapter 1

2 Neural Networks • 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 323 -670 Artificial Intelligence 20 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. 323 -670 Artificial Intelligence 21 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. 323 -670 Artificial Intelligence 22 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. 323 -670 Artificial Intelligence 23 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. 323 -670 Artificial Intelligence 24 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. 323 -670 Artificial Intelligence 25 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. 323 -670 Artificial Intelligence 26 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. 323 -670 Artificial Intelligence 27 Chapter 1

Neural Network 323 -670 Artificial Intelligence 28 Chapter 1

Neural Network 323 -670 Artificial Intelligence 29 Chapter 1

323 -670 Artificial Intelligence 30 Chapter 1

323 -670 Artificial Intelligence 31 Chapter 1

323 -670 Artificial Intelligence 32 Chapter 1

323 -670 Artificial Intelligence 33 Chapter 1

323 -670 Artificial Intelligence 34 Chapter 1

323 -670 Artificial Intelligence 35 Chapter 1

A Neuron x 0 w 0 x 1 w 1 xn - mk å f wn Input weight vector x vector w weighted sum output y Activation function • The n-dimensional input vector x is mapped into variable y by means of the scalar product and a nonlinear function mapping 323 -670 Artificial Intelligence 36 Chapter 1

Multi-Layer Perceptron Output vector Output nodes Hidden nodes wij Input nodes Input vector: xi

Neural Network Training: A Detailed View 323 -670 Artificial Intelligence 38 Chapter 1

Neural Networks • Advantages – prediction accuracy is generally high – robust, works when training examples contain errors – output may be discrete, real-valued, or a vector of several discrete or real-valued attributes – fast evaluation of the learned target function • Criticism – long training time – difficult to understand the learned function (weights) – not easy to incorporate domain knowledge 323 -670 Artificial Intelligence 39 Chapter 1

Network Training • The ultimate objective of training – obtain a set of weights that makes almost all the tuples in the training data classified correctly • Steps – Initialize weights with random values – Feed the input tuples into the network. . . one by one – For each unit • Compute the net input to the unit as a linear combination of all the inputs to the unit • Compute the output value using the activation function • Compute the error • Update the weights and the bias

Feed-Forward Neural Network 323 -670 Artificial Intelligence 41 Chapter 1

Neural Network Training: A Conceptual View 323 -670 Artificial Intelligence 42 Chapter 1

3 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. 323 -670 Artificial Intelligence 43 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. 323 -670 Artificial Intelligence 44 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 theorem is verified for the smallest admissible value of the integer. Then it is proven that if theorem is true for any value of the integer, it is true for the next greater value. The final proof contains the two parts. 323 -670 Artificial Intelligence 45 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. 323 -670 Artificial Intelligence 46 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 323 -670 Artificial Intelligence 47 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. 323 -670 Artificial Intelligence 48 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. 323 -670 Artificial Intelligence 49 Chapter 1

4 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) 323 -670 Artificial Intelligence 50 Chapter 1

Robotics • A legged game from Robo. Cup 2004 in Lisbon, Portugal • Team ENSCO's entry in the first Grand Challenge, DAVID 323 -670 Artificial Intelligence 51 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. 323 -670 Artificial Intelligence 52 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. 323 -670 Artificial Intelligence 53 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. 323 -670 Artificial Intelligence 54 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. ) 323 -670 Artificial Intelligence 55 Chapter 1

Robotics 323 -670 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. ) 56 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. ) 323 -670 Artificial Intelligence 57 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. 323 -670 Artificial Intelligence 58 Chapter 1

Robotics • ASIMO, • a humanoid robot manufactured by Honda. 323 -670 Artificial Intelligence 59 Chapter 1

5 Computer Vision 323 -670 Artificial Intelligence 60 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. 323 -670 Artificial Intelligence 61 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. 323 -670 Artificial Intelligence 62 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. 323 -670 Artificial Intelligence 63 Chapter 1

Computer Vision based biological species identification systems 323 -670 Artificial Intelligence 64 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) 323 -670 Artificial Intelligence 65 Chapter 1

323 -670 Artificial Intelligence 66 Chapter 1

Image Processing Fields 323 -670 Artificial Intelligence 67 Chapter 1

• Image – An image is a two-dimensional signal Digital Image Processing 323 -670 Artificial Intelligence 68 Chapter 1

Digital Image Processing • Digital Image – A digital image is a two-dimensional signal with a countable domain and a countable range 323 -670 Artificial Intelligence 69 Chapter 1

Histogram 323 -670 Artificial Intelligence 70 Chapter 1

2 323 -670 Artificial Intelligence 71 Chapter 1

Image Enhancement 323 -670 Artificial Intelligence 72 Chapter 1

Image Segmentation Line Detection • horizontal, . . . +45 degree, . . vertical. . . and -45 degree masks • Horizontal mask will result with max response when a line passed through the middle row of the mask with a constant background. • the similar idea is used with other masks. • note: the preferred direction of 73 each mask is weighted with Chapter a larger 323 -670 Artificial Intelligence 1 coefficient. . (i. e. , 2) than other possible directions.

Example 323 -670 Artificial Intelligence 74 Chapter 1

7 Expert Systems • expert system n. Computer Science. • A program that uses available information, heuristics, and inference to suggest solutions to problems in a particular discipline. 323 -670 Artificial Intelligence 75 Chapter 1

Expert Systems • 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. 323 -670 Artificial Intelligence 76 Chapter 1

Expert Systems • 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. 323 -670 Artificial Intelligence 77 Chapter 1

Expert Systems • 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. 323 -670 Artificial Intelligence 78 Chapter 1

Expert Systems 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 323 -670 Artificial Intelligence 79 Chapter 1

Reference Artificial Intelligence second edition, Elaine Rich and Kevin Knight, Mc. Graw-Hill Inc. , 1991. James A. O’Brien and George M. Marakas, Management Information Systems, 8 th edition, Mc. Graw-Hill /Irwin, 2008 Jim Miller 323 -670 Artificial Intelligence 80 Chapter 1

Q&A 323 -670 Artificial Intelligence 81 Chapter 1

http: //www. thai 2 english. com 323 -670 Artificial Intelligence 82 Chapter 1

323 -670 Artificial Intelligence 83 Chapter 1

http: //translate. google. com 323 -670 Artificial Intelligence 84 Chapter 1

http: //translate. google. com 323 -670 Artificial Intelligence 85 Chapter 1

323 -670 Artificial Intelligence 86 Chapter 1

Text to speech 323 -670 Artificial Intelligence 87 Chapter 1

http: //teachrose. com/rose/src/talk. php 323 -670 Artificial Intelligence 88 Chapter 1

Expert systems 323 -670 Artificial Intelligence 89 Chapter 1

323 -670 Artificial Intelligence 90 Chapter 1

Car Tracking http: //www. youtube. com/watch? v=-e 21 jp. Whq. VM&feature=related 323 -670 Artificial Intelligence 91 Chapter 1

Robotics http: //www. youtube. com/watch? v=2 GBMAt. Ga. Gdg 323 -670 Artificial Intelligence 92 Chapter 1

Virtual Reality 323 -670 Artificial Intelligence 93 Chapter 1

Car Tracking http: //www. youtube. com/watch? v=OKSod. Rh. Ev. A 8&feature=related 323 -670 Artificial Intelligence 94 Chapter 1

OLAP http: //www. tonprikinfo. org/application/index. php? id=16 323 -670 Artificial Intelligence 95 Chapter 1

323 -670 Artificial Intelligence 96 Chapter 1

323 -670 Artificial Intelligence 97 Chapter 1

KM 323 -670 Artificial Intelligence 98 Chapter 1

Gotoknow. org 323 -670 Artificial Intelligence 99 Chapter 1