Expert Systems

Expert Systems

Chuleeporn Changchit (Texas A&M University – Corpus Christi, USA)
Copyright: © 2008 |Pages: 7
DOI: 10.4018/978-1-59904-881-9.ch053
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Abstract

While technology and human abilities have evolved over the years, individuals still have limitations in their abilities to accomplish certain tasks. This may be due to limits on financial or cerebral resources. Information needs have expanded and evolved as well. With the spurring of globalization and flatter hierarchies in organizations, it has become imperative that individuals are able to analyze, in shorter periods of time, information that is more complicated and wider in scope.

Key Terms in this Chapter

Inference Engine: A program’s protocol for navigating through the rules and data in a knowledge system in order to solve the problem. The major task of the inference engine is to select and then apply the most appropriate rule at each step as the expert system runs, which is called rule-based reasoning.

Knowledge: A collection of specialized facts, procedures, and judgment rules.

Artificial Intelligence: A field of study and development that attempts to imitate the functioning of the human mind, principally through the use of computer technology.

Knowledge Representation: A formalized structure and sets of operations that embodies the descriptions, relationships, and procedures provided in an expert system. The process considers how to represent the knowledge in the system such that it can be used to solve problems.

Knowledge Inference: The process of programming a computer in such a way that it can make reference in an attempt to imitate the reasoning behaviors of the experts.

Expert System: A computer-based system that uses captured human knowledge to solve problems that ordinarily require human experts.

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