Expert Systems

Topics: Knowledge engineering, Decision theory, Expert system Pages: 5 (1780 words) Published: May 12, 2011
What is an expert system?
The most recent addition to the circle of information systems is the expert system. Expert systems are associated with an area of research known as artificial intelligence. We introduced expert systems and artificial intelligence in the World of computers.” Artificial intelligence is the ability of a computer to reason, to learn, to strive for self-improvement, and to simulate human sensory capabilities. Like the DSS, expert systems are computer-based systems that help managers resolve problems or make better decisions. However, an expert system does this with a decidedly different twist. It is an interactive computer-based system that responds to questions, asks for clarification, makes recommendations, and generally helps the user in the decision-making process. In effect, working with an expert system is much like working directly with a human expert to solve a problem because the system mirrors the human thought process. It even uses information supplied by a real expert in a particular field such as medicine, taxes, or geology. An expert system applies preset IF-THN rules to solve a particular problem, such as determining a patient’s illness. Like management information systems and decision support systems, expert systems rely on factual knowledge, but expert systems also rely on heuristic knowledge such as intuition, judgment, and inferences. Both the factual knowledge and the heuristic rules of thumb are acquired from a domain expert, an expert in a particular field, such as jet engine repair, life insurance, or property assessment. The expert system uses this human-supplied knowledge to model the human taught process within a particular area of experience .Once completed, a knowledge-based system can approximate the logic of a well-informed human decision maker. Technically speaking; an expert system is the highest form of a knowledge-based system. In practice, the terms expert system and knowledge-based systems are used interchangeably. The less sophisticated knowledge based system is called assistant systems. An assistant system helps users make relatively straightforward decisions. Assistant systems are usually implemented to reduce the possibility that the end user will make an error in judgment rather than to resolve a particular problem. In effect, expert system simulates the human thought process. To varying degrees, they can reason, draw inferences, and make judgments. Here is how an expert system works. Let’s use a medical diagnosis expert system as an example. Upon examining a patient, a physician might use an expert diagnosis system to get help in diagnosing the patient’s illness or, perhaps, to get a second opinion. First the doctor would relate the symptoms to the expert system: male, age 10, temperature of 103, and swollen glands about the neck. Needing more information, the expert system might ask the doctor to examine the parotid gland for swelling. Upon receiving an affirmative answer, the system might ask a few more questions and even ask for lab reports before giving a diagnosis. A final question for the physician might be whether the patient had been previously afflicted with or immunized for parotitis. Based on the information, the expert system would diagnose the illness as parotitis, otherwise known as the mumps. In recent years expert systems have been developed to support decision makers in a broad range of disciplines, including medical diagnosis, oil exploration, financial planning, tax preparation, chemical analysis, surgery, locomotive repair, weather prediction, computer repair, troubleshooting satellite, computer systems configuration, nuclear-power plant operation, newspaper layout, interpreting government regulations, and many others.

The benefits of an expert system are somewhat different from those of other decision support system s and of management information systems. An expert system enables...
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