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The Landscape of Expert System is a
random landscape of terms about an Artificial Intelligence application that
uses a knowledge base of human expertise for problem solving.
An expert system, also known as a knowledge
based system, is a computer program that contains some of the
subject-specific knowledge, and contains the knowledge and analytical skills
of one or more human experts. This class of program was first developed by
researchers in artificial intelligence during the 1960s and 1970s and
applied commercially throughout the 1980s. The most common form of expert
systems is a program made up of a set of rules that analyze information
(usually supplied by the user of the system) about a specific class of
problems, as well as providing mathematical analysis of the problem(s), and,
depending upon their design, recommend a course of user action in order to
implement corrections. It is a system that utilizes what appear to be
reasoning capabilities to reach conclusions.
A related term is wizard. A wizard is an interactive computer program that
helps a user solve a problem. Originally the term wizard was used for
programs that construct a database search query based on criteria supplied
by the user. However some rule-based expert systems are also called wizards.
Other "Wizards" are a sequence of online forms that guide users through a
series of choices, such as the ones which manage the installation of new
software on computers, and these are not expert systems.
Types of problems solved by expert systems
Expert systems are most valuable to organizations that have a high-level
of know-how experience and expertise that cannot be easily transferred to
other members. They are designed to carry the intelligence and information
found in the intellect of experts and provide this knowledge to other
members of the organization for problem-solving purposes.
Typically, the problems to be solved are of the sort that would normally be
tackled by a medical or other professional. Real experts in the problem
domain (which will typically be very narrow, for instance "diagnosing skin
conditions in human teenagers") are asked to provide "rules of thumb" on how
they evaluate the problems, either explicitly with the aid of experienced
systems developers, or sometimes implicitly, by getting such experts to
evaluate test cases and using computer programs to examine the test data and
(in a strictly limited manner) derive rules from that. Generally expert
systems are used for problems for which there is no single "correct"
solution which can be encoded in a conventional algorithm â€” one would not
write an expert system to find shortest paths through graphs, or sort data,
as there are simply easier ways to do these tasks.
Simple systems use simple true/false logic to evaluate data, but more
sophisticated systems are capable of performing at least some evaluation
taking into account real-world uncertainties, using such methods as fuzzy
logic. Such sophistication is difficult to develop and still highly
Expert System applications:
Intelligent Manufacturing and Engineering
Finance and Investments
Estate and insurance planning
Accounting and Auditing
Designing Innovative Business Systems
Expert Systems for Marketing: Interactive
Expert Systems for Management of Natural
Medical Expert Systems
Non Defense Government Services and
Military Expert Systems Applications