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An expert system is an example of a knowledge-based system. Expert systems were the first commercial systems to use a knowledge-based architecture. In general view, an expert system includes the following components: a knowledge base, an inference engine, an explanation facility, a knowledge acquisition facility, and a user interface. [48] [49]
These issues led to the second approach to knowledge engineering: the development of custom methodologies specifically designed to build expert systems. [1] One of the first and most popular of such methodologies custom designed for expert systems was the Knowledge Acquisition and Documentation Structuring (KADS) methodology developed in Europe ...
The first knowledge-based systems were primarily rule-based expert systems. These represented facts about the world as simple assertions in a flat database and used domain-specific rules to reason about these assertions, and then to add to them. One of the most famous of these early systems was Mycin, a program for medical diagnosis.
Expert systems were one of the first successful applications of artificial intelligence technology to real world business problems. [1] Researchers at Stanford and other AI laboratories worked with doctors and other highly skilled experts to develop systems that could automate complex tasks such as medical diagnosis .
In the field of artificial intelligence, an inference engine is a software component of an intelligent system that applies logical rules to the knowledge base to deduce new information. The first inference engines were components of expert systems. The typical expert system consisted of a knowledge base and an inference engine.
A classic example of a production rule-based system is the domain-specific expert system that uses rules to make deductions or choices. [1] For example, an expert system might help a doctor choose the correct diagnosis based on a cluster of symptoms, or select tactical moves to play a game.
The engine used for automated reasoning in expert systems were typically called inference engines. Those used for more general logical inferencing are typically called theorem provers. [2] With the rise in popularity of expert systems many new types of automated reasoning were applied to diverse problems in government and industry.
2012. Made fellow of the Computer History Museum "for his pioneering work in artificial intelligence and expert systems." [22] 2013. IEEE Computer Society Computer Pioneer Award for "pioneering work in Artificial Intelligence, including development of the basic principles and methods of knowledge-based systems and their practical applications".