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Transcript
Artificial Intelligence
Intelligent?
What is intelligence?

computational part of the ability to achieve
goals in the world
somewhere, something went wrong
What is AI?
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Computational models of human behavior?
Computational models of human “thought” process?
Computational systems that behave intelligently?
Computational systems that behave rationally !
Rationality:
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Perceiving the world around it,
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a rational agent selects an action
to maximize the performance measure
Using
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Evidence provided in perception sensors
Built in knowledge of the agent
Applications of AI
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Video games, Robocup, NERO
Theorem proving
Speech recognition
Understanding natural language (stories)
Machine translation (English-Russian)
Robotics (Computer vision)
Machine translation
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The spirit is willing but the flesh is weak
English – Russian - English

The spirit is willing but the flesh is weak
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The vodka is strong but the meat is rotten
AI applications (contd.)
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Driving autonomous vehicles
Tactical guidance system for military aircraft
Satellite meta command system
Automatic operation of trains
Robots for micro-surgery
AI in electrical gadgets
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Navigation system for automatic cars
Cruise control for automobiles
Single button control of washing machines
Camera autofocus
Back light control for camcorders
Auto motor control of vacuum cleaners
Camera aiming for sporting events
Decision support systems
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Medical reasoning systems
Planning rocket launching, large assemblies
Intelligent tutoring systems
Fault diagnosis in power plants
Direct marketing
Fraud detection for finance
Stock market predictions
AI pioneers
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Alan Turing(1912-1954)
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Marvin Minsky (MIT)
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Father of computer science
Turing test for AI
Built first Neural network computer SNARC
John McCarthy ( Stanford University )
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Developed LISP, AI programming language
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http://nerogame.org/
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General issues and applications of AI ,
Problem solving,
Search strategies,
Intelligent searching
Course contents
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, Knowledge Representation,
First order predicate logic, ,
Frames
Conceptual dependency
 Game playing
 Problem solving using Planning,
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Uncertainty handling,
Fuzzy Logic based inferencing,
Machine learning – introduction to neural
networks and genetic algorithms,
Expert Systems,
Natural Language Processing
Reference books:
1.
2.
Artificial Intelligence – A modern approach,
S. Russell and P.Norvig, Pearson
Education.
Artificial Intelligence, Elaine Rich and K
Knight, Tata McGraw Hill, reprint 2003
Evaluation:


Minor I
Minor II
Quiz tests and Major test:
Assignments:
20%
20%
40%
20%