1. Expert Systems
Expert Systems are computerized advisory programs that imitate the reasoning process of experts. They consist of a knowledge base and a set of rules for applying that knowledge base to a particular situation.
EXPERT SYSTEMS
The system uses IF statements and user answers to questions in order to reason just like a human does.
It takes something the users doesn’t know and applies rules to indicate what to do.
Expert Systems: to determine what is “known.”

2. Easy Diagnosis Medical Expert System

3. WHAT EXPERT SYSTEMS CAN DO
Can handle massive amounts of information and they can
Can from complex relationships
Can explain their reasoning or suggested decisions
Provide in decision making.
Improve customer service.
Reduce errors and costs.
Provide

4. WHAT EXPERT SYSTEMS CAN’T DO
Handle all types of domain expertise. Human experts might not fully be aware of the process that they use. Can’t put everything into machine form.
Can’t solve problems in areas not designed for. Can’t
Apply or judgment to a problem

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Expert Systems Perform and Tasks Like
Expert System used by American Express’ Optima Card program.
Auditing and tax planning
Diagnosing illnesses
Managing forest resources
Evaluate credit and loan applications
Computer help desk diagnosis assistance
Rules to follow when directing air traffic
VB Loan System
Smartflow
Exsys Corvid
Which Dog Breed is best for you?
Marathon Race Advisor
Albuquerque Restaurant Advisor
Web Support
Camcorder Selection
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6. Ethical Questions and the Use of Expert Systems
An expert system will act as it is programmed. If you program in bias, then the system will be biased.
The expert system is consistent, which is easily defended in court.
Can distinguish between good and bad, but may not be able to distinguish between degrees of good.

7. Expert Systems are computerized advisory programs that imitate the reasoning process of experts.
EXPERT SYSTEMS apply rules to solve a problem.
Expert Systems: ask a series of questions to determine what is “known.”
Neural Networks mimic the way the brain works, analyzing large quantities of data and information to establish patterns and infer relationships.
They
They can “see” subtle, hidden and newly emerging patterns within large amounts of complex data.

8. A NEURAL NETWORK
is an artificial intelligence system which is capable of learning because it’s patterned after the human brain. Uses parallel processors.
A neural network simulates the human ability to classify things based on the experience of seeing many examples.
Learn by

9. NEURAL NETWORKS
Typically used to combat attempts at fraud
Credit card fraud or insurance fraud.
Able to detect money laundering attempts.
Working in conjunction with X-ray machines, can be used to detect weapons and other forbidden items.
Often used to make investment decisions (stocks, bonds, futures markets, etc.)
Can also detect inefficiencies in financial markets
Learn by looking at a data set and finding patterns in it.

10. A Neural Network Can Perform Tasks Like
Distinguishing different chemical compounds
D in human tissue that may signify disease
A to detect forgeries. De
Track habits of insurance customers and predict which ones might not renew their policies
Virus Detection Software by IBM
Neugent monitors 1,200 data points in the Allstate Insurance network every 5 seconds, trying to predict a potential problem in/with the network.

11. Neural networks attempt to mimic the structure and functioning of the human brain. They contain input, output and hidden layers. The hidden layers use various weights of strength to As the system , it can change the classification weights.
Neural networks can adjust or change themselves over time based upon data input regarding successful and unsuccessful mortgage applications. Neural networks as they “learn”. Expert systems

12. Neural Networks serve as Systems
Allows the computer to or it receives.
There are computer games with learning abilities.
20Questions
F and neural networks are often combined to express complicated and concepts (that are and ambiguous) in a form that makes it possible to simplify the problem and apply rules with some degree of certainty.

13. Fuzzy Logic
Fuzzy Logic: a special field of computer science that and does not require conditions to be
A mathematical method of handling information so that ambiguous information such as “ ” or “ ” or other “non-exact areas usable in computer systems
Applications
Google’s search engine (your perception of a topic frames your query)
Washing machines that wash until the water is “clean”
A and subway/tram control systems
A cameras
Temperature sensors attached to furnace controls
Medical equipment that based upon patient vital signs.

14. EXPERT SYSTEMS apply rules to solve a problem.
The system uses IF statements and user answers to questions in order to reason just like a human does.
It takes something the users doesn’t know and applies rules to indicate what to do.
Expert Systems: ask a series of questions to determine what is “known.”
NEURAL NETWORKS recognize/learn patterns and can apply that learning to the unknown.
It is either taught by someone or teaches itself. After it is taught to recognize the pattern, it can adjust itself to reflect new learning.
Neural networks: system is “guessing” based upon examples and patterns found in the data set- trying to figure out what category something fits in.
GENETIC ALGORITHMS generate several generations of solutions, with each generation resulting in a better solution to the problem.