Expert system

see also: rule engines

An expert system is a computer program that creates the judgment and behavior of a human or an organization that has expert knowledge and experience in a particular field. Expert systems use human knowledge to solve problems that normally requires human intelligence. This expert knowledge is stored as data or rules within the computer and is called when needed to solve problems. Expert systems differ from conventional programs that perform tasks using decision-making logic, basic algorithms and border conditions. The program knowledge is typically fixed and must be changed as knowledge advance. Expert systems are part of a general category of computer application known as artificial intelligence. To design an expert system, one needs a knowledge engineer, an individual who studies how human experts make decisions and translates the rules into terms that a computer can understand. Advantages: . Provides steady answers recurring decisions, processes and task . Holds and maintains important levels of information . Can work round the clock . Can serve more users at a time Disadvantages: . Cannot make creative responses as human expert would in unusual situation . Errors may occur in the knowledge base, and lead to wrong decision . Cannot get used to changing environments, unless knowledge base is changed . Lacks common sense needed in some decision making

Application: . Diagnosis and Troubleshooting of Devices and Systems of All Kinds . Planning and Scheduling . Arrangement of artificial objects from subassemblies . Knowledge publishing Benefits: . A speed-up of human professional or semi-professional work . Within companies, major internal cost savings . A good example of a new product . Better quality of decision making

An expert system is typically composed of at least three primary components. These are the inference engine, the knowledge base, and the rule base.