programming-for-dummies

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Problem Solving
The ultimate goal of chess-playing computers is to beat a human chess grandmaster.
In 2005, a computer specially built for playing chess, dubbed Hydra,
defeated grandmaster Michael Adams. In 2006, another dedicated chessplaying
computer called Deep Fritz defeated Vladimir Kramnik. Computers
have now proven they’re capable of defeating chess grandmasters, so this goal
of AI has finally been achieved, although the lessons learned by beating chess
grandmasters aren’t easily transferred to solving other types of problems.
Expert systems
If computers are good at figuring out how to solve problems within a limited
domain, computer scientists reasoned that computers could also be useful
for helping humans solve problems as well. The type of program designed to
help humans solve problems is an expert system.
The idea behind an expert system is to capture the knowledge of a real human
expert and store it in a program, essentially cloning the human expert’s
thought process. Instead of consulting a human expert for help, someone can
just consult the expert system instead.
One of the first expert systems developed was Mycin, which was developed by
Stanford University. The goal of Mycin is to help humans diagnose infectious
blood diseases and recommend the proper type and dosage of antibiotics.
Like all expert systems, Mycin worked by asking questions to get information
about the problem. By gathering more information about the problem, Mycin
could keep narrowing its list of questions until it could identify a possible solution.
In tests, Mycin actually proved more accurate than Stanford’s own medical
staff in solving problems. However, Mycin was never used in actual practice
for legal reasons. If Mycin makes a mistake, who’s responsible — the expert
system programmers or the doctor relying on the expert system’s advice?
An expert system consists of three parts, as shown in Figure 4-1:
✦ A knowledge base — stores the information about a particular subject.
✦ An inference engine — manipulates the information stored in its
knowledge base.
✦ A user interface — lets users interact with the knowledge base and
inference engine.