csce101 –chapter 8 (continued) tuesday, december 5, 2006
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CSCE101 –Chapter 8 (continued)
Tuesday, December 5, 2006
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Information Systems
• Office Information Systems
• Transaction Processing Systems
• Management Information Systems
• Decision Support Systems
• Executive Support Systems
• Expert Systems
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Experts System Components
• End user, problem domain expert, knowledge engineer
• Components of an expert system– Knowledge Base– Inference Engine– User Interface
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Inference
• Given that certain premises are true, one can deduce a conclusion that is also true.
Example #1:All men are mortal Socrates is a man ------------------ Therefore Socrates is mortal.
Example #2:Given the output from two queries against a personnel database:1. How many women are in Department X:
Result: 12. What is the average salary of the women in Department x?
Result: $60,000Conclusion: One now knows the exact salary of the only woman in Department X
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Other Uses of AI
• Natural language processing
• Intelligent agents
• Pattern recognition
• Fuzzy logic
• Virtual reality & simulation devices
• Robotics
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Natural Language Processing
Brute force processing = Generating all possible answers + selection of best answer
Ex. #1: Word substitution until a meaningful sentence occurs:English: “The spirit is willing, but the flesh is weak.”
Russian: “The wine is agreeable, but the meat is spoiled.”
Ex. #2: Computers that play chess
Ex. #3: Decryptors
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Intelligent Agents
• Act autonomously on behalf of the user (ex.: bots, crawlers, spiders).
• Data mining capabilities
• Learning and adapting
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Pattern Recognition
• Recognition of some kind of pattern in multimedia data or text data.
Ex. #1: Face recognition software
Ex. #2: Data mining
• AI winters
• Pattern recognition software became an important research area after 9/11
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Fuzzy Logic
• Predicate logic vs. fuzzy logic
• Degrees of participation in a set
Ex. #1 – In which room are you standing?
Ex. #2 – Programming elevators in order to optimize traffic flow
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Virtual Reality and Simulation Devices
• Computer-generated sensory data
• Virtual reality programs create output that simulates some aspect of reality. Can be used for entertainment or training purposes.
• Simulators are specifically designed to train a response into the user (ex.: surgeons, pilots)
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Robots
• Robots perform physical tasks that would normally be done by a human
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Weak AI vs. Strong AI
• Weak AI – Conventional AI– May include brute-force calculations– Finite reasoning capability
• Strong AI – Computational Intelligence– Computer can “learn”– Chinese Room thought experiment– Edsgar Dijkstra –
• “Debating as to whether a computer can actually think is about as relevant as debating whether a submarine is really swimming”
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Weak AI vs. Strong AI (continued)
• Strong AI – Computational Intelligence– Attempts at implementing Strong AI
• Neural networks• Genetic algorithms• Cyborgs
– Turing test– Captchas
• Ethics in AI – AI can’t be value free because it is built by humans
• AI run amok is standard fare for science fiction.• Many ideas for strong AI come from the
discipline of epistemology.
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Weak AI vs. Strong AI (continued)
• A branch of philosophy known as ontology is also studied by AI researchers
• General purpose AI applications vs. specific purpose AI applications