CSCE101 –Chapter 8 (continued)

Tuesday, December 5, 2006

Information Systems

• Office Information Systems

• Transaction Processing Systems

• Management Information Systems

• Decision Support Systems

• Executive Support Systems

• Expert Systems

Experts System Components

• End user, problem domain expert, knowledge engineer

• Components of an expert system– Knowledge Base– Inference Engine– User Interface

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

Other Uses of AI

• Natural language processing

• Intelligent agents

• Pattern recognition

• Fuzzy logic

• Virtual reality & simulation devices

• Robotics

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

Intelligent Agents

• Act autonomously on behalf of the user (ex.: bots, crawlers, spiders).

• Data mining capabilities

• Learning and adapting

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

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

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)

Robots

• Robots perform physical tasks that would normally be done by a human

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”

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.

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