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The Expert Systems Approach to Artificial Intelligence

The “top-down” approach to Artificial Intelligence tries to copy the brain's behavior through the use of computer programs. The expert system is such a program. It stores large quantities of information and uses set rules to manipulate and assess data for the purpose of providing analysis and sometimes even solutions to correct the problems it detects. As such, expert systems act like doctors who cure patients by using logic and information.

The great advantage of expert systems is that their practical applications provide portable, in-depth knowledge to locations and situations that are in need of expert opinions but are, for whatever reason, unable to receive them. The systems aid decision-makers by supplying them with pertinent and extensive information for objectives ranging from problem solving to strategic planning. For example, a small-town lawyer can bring to bear the experience and expertise of his colleagues around the country when assembling a complicated case.

Simple expert systems use binary logic for data assessment. More sophisticated systems are able to apply methods like fuzzy logic, but such systems are hard to design and, therefore, quite imperfect. And although expert systems have demonstrated their adaptability to practical applications, the current downside of the systems is the narrowness of their scope of knowledge. The specificity of expertise makes them vulnerable to mistakes that human experts would not make.

See also:
The Neural Network Approach to Artificial Intelligence

Web Resources On The Expert Systems Approach to Artificial Intelligence

American Association for Artificial Intelligence
Wikipedia: AI

Book Resources On The Expert Systems Approach to Artificial Intelligence

Artificial Intelligence: A Modern Approach by Stuart J. Russel and Peter Norvig
Comparative Cognitive Robotics: Computation and Human Experience by Agre, Philip E., et al

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