lect # 2

Artificial Intelligence(AI)

Lecture No. 2

Rahman AliRahman AliLecturer in Computer Science,

Quaid-e-Azam College of Commerce, University of Peshawar

[email protected]

Agenda

Applications of AI Game playing General problem solving Expert system Natural language Processing Computer vision Robotics Education Others

References End

Artificial Intelligence by Rahman Ali, Lect: QACC,UOP

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AI applications - Games


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Why games are important Games are integral attribute of human beings They are perfect for learning and fun, develop

conscious reaction and satisfy human's thirst of knowledge and curiosity.

It develops the puzzle solving capability of human

So, if computers are going to mimic people they should be able to play games.


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Playing gamesComputers can play the following, and a

lot of others, games and solve the puzzles

Initial problems: Less memory (knowledge base) Slow processing speed


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Chess, Checker and Go


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B<=40. m<=100 8x8, 10x10, 12x12 b<=300

Mikhael Goikhman (2004)

AI applications – General problem solving

Types of problems:DeterministicNon-deterministic

>> AI is concerned with solving non-deterministic problem


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AI applications – General problem solving General problem solving


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AI applications – General problem solving General problem solving programs:

MAC’s SYmbolic Manipulator (MACSYMA) is a computer algebra system developed from 1968 to 1982 at MIT as part of Project MAC It was the first comprehensive symbolic mathematics system that can perform

Theorems proof Formula reductions and more than 500 mathematical operations

General Problem Solver (GPS) GPS created in 1959 by Herbert Simon, J.C. Shaw, and Allen Newell intended to

work as a universal problem solver machine. Any formalized symbolic problem can be solved for instance:

theorems proof, geometric problems and chess playing

Limitation: it could not solve any real-world problem


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AI applications – Expert Systems

An expert system is a computer program that is designed to hold the accumulated knowledge of one or more domain experts.


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Applications of Expert Systems

PROSPECTOR:Used by geologists to

identify sites for drilling or mining

PUFF:Medical system

for diagnosis of respiratory conditions


DESIGN ADVISOR:Gives advice to designers of

processor chips

MYCIN:Medical system for diagnosing blood

disorders. First used in 1979


DENDRAL: Used to identify the structure of chemical compounds.

First used in 1965

LITHIAN: Gives advice to archaeologists examining

stone tools

Components of an Expert System

The knowledge base is the collection of facts and rules which describe all the knowledge about the problem domain

The inference engine is the part of the system that chooses which facts and rules to apply when trying to solve the user’s query

The user interface is the part of the system which takes in the user’s query in a readable form and passes it to the inference engine. It then displays the results to the user.

Components of an Expert System


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Why use Expert Systems?

Experts are not always available. An expert system can be used anywhere, any time.

Human experts are not 100% reliable or consistent

Experts may not be good at explaining decisions

Cost effective

Problems with Expert Systems

Limited domain Systems are not always up

to date, and don’t learn No “common sense” Experts needed to setup

and maintain system

Legal and Ethical Issues

Who is responsible if the advice is wrong?The user?The domain expert?The knowledge engineer?The programmer of the expert system

shell?The company selling the software?

Expert Systems on the Web

Whale watcher http://www.aiinc.ca/demos/whale.html

Forecasting & Planning Solutions to businesses http://www.vanguardsw.com/decisionscript/examples.htm

Knowledge automation Expert System technology http://www.exsys.com/demomain.html

Diagnosing Why a Car Won't Start http://www.expertise2go.com/webesie/car

Choosing a Basic Dinner Wine http://www.expertise2go.com/webesie/wine

AI Application: Natural language processing (NLP) Natural language processing (NLP) is a

subfield of artificial intelligence and computational linguistics. It studies the problems of automated understanding and generation of natural human languages

OR Getting computers to understand and

communicate in everyday language is known as natural language processing.


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AI Application: Natural language processing


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Natural language processing (NLP)

Natural Language Understanding (NLU) Natural-language-understanding systems

convert samples of natural human language into more formal representations that are easier for computer programs to manipulate.

Natural Language Generation (NLG) Natural-language-generation systems convert

information from computer databases into normal-text or sounding human language.


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Natural language interface


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Components of an NLP System


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Application of AI: Vision

Vision is the process of discovering what is present in the world and where it is by looking.

Application of AI: Computer Vision Computer Vision is the study of analysis of pictures and

videos with the help of machines (computers) in order to achieve results similar to those as by men.

Or Computer vision is the sub field of Artificial intelligence

which is focused on "teaching machines how to see”.

Computer Vision: Example

Finding People in images

Problem 1: Given an image “Img” on next slide

Question: Does “Img” contain an image of a person?

“Yes” Instances

“No” Instances

Computer Vision System (components)


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Application of AI: Robotics


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Application of AI: Robotics

Robotics is the branch of technology that deals with the design, construction, operation, structural disposition (outlook), manufacture and application of robots.

Robotics is related to the sciences of: electronics, engineering, mechanics, and Computer Science (software engineering)


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Application of AI: Education

CBT: Computer Based Training Computer can be used for training purpose and

acts as an intelligent tutor. Types of CBT:

Conventional CBT: Sequence of instructional materials are presented to train the

employee Present a fixed contents to different background of students. Example: canned

AI-based CBT: Can adjust tutor according to experience, knowledge and

weaknesses of the students. Student can also learn from expert systems


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Applications of AI: Other fields

AI-based automatic programming: Idea:

the programmer uses natural language statement and the AI algorithm convert it into any language code or direct to the machine code.

Computer Aided Design (CAD): Mechanical, electrical and architectural engineers

use AI techniques to design products and systems in record time with minimum efforts.

Finance: Stock exchange, bonds etc


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References

Crash Course in Artificial Intelligence and Expert systems by Louise E. Frenzel.

Chapter No.1

Artificial Intelligence - A Modern Approach 3rd ed - S. Russell, P. Norvig (Prentice-Hall, 2010) WW

Chapter No.1


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Natural Language Processing (NLP) by Rahman Ali, Lect: QACC, UOP

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Question????

Natural Language Processing (NLP) by Rahman Ali, Lect: QACC, UOP

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The end

lect # 2

Technology

games computers

important games

rahman ali lecturer

agenda applications

computer science

capability of human

humans thirst of knowledge

general problem