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Artificial Intelligence(AI)
Lecture No. 2
Rahman AliRahman AliLecturer in Computer Science,
Quaid-e-Azam College of Commerce, University of Peshawar
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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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AI applications - Games
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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AI applications - Games
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)
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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
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Applications of Expert Systems
DESIGN ADVISOR:Gives advice to designers of
processor chips
MYCIN:Medical system for diagnosing blood
disorders. First used in 1979
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Applications of Expert Systems
DENDRAL: Used to identify the structure of chemical compounds.
First used in 1965
LITHIAN: Gives advice to archaeologists examining
stone tools
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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.
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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
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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
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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?
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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
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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.
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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”.
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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?
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“Yes” Instances
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“No” Instances
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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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Question????
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The end