Expert Systems

Introduction:-Expert systems are knowledge-based systems that contain expert knowledge. For example, an expert system for diagnosing car faults has a knowledge base containing rules for checking a car and finding faults in the same way an engineer would do it. An expert system is a program that can provide expertise for solving problems in a defined application area in the way the experts do.

Expert systems have facilities for representing existing expert knowledge, accommodating existing databases, learning and accumulating knowledge during operation, learning new pieces of knowledge from existing databases, making logical inferences, making decisions and giving recommendations, communicating with users in a friendly way (often in a restricted natural language), and explaining their"behaviour" and decisions. The explanation feature often helps users to understand and trust the decisions made by an expert system. Learning in expert systems can be achieved by using machine-learning methods and artificial neural networks.

Expert systems have been used successfully in almost every field of human activity, including engineering, science, medicine, agriculture, manufacturing, education and training, business and finance, and design. By using existing information technologies, expert systems for performing difficult and important tasks can be developed quickly, maintained cheaply, used effectively at many sites, improved easily, and refined during operation to accommodate new situations and facts.

There are two easily distinguishable sides of an expert system the expert's side, and the users' side. Experts transfer their knowledge into the expert system. The users make use of it.