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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 ...
expert: describes only the task the system is designed for – its purpose is to aid replace a human expert in a task typically requiring specialised knowledge knowledge-based : refers only to the system's architecture – it represents knowledge explicitly, rather than as procedural code
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.
Knowledge acquisition is the process used to define the rules and ontologies required for a knowledge-based system. The phrase was first used in conjunction with expert systems to describe the initial tasks associated with developing an expert system, namely finding and interviewing domain experts and capturing their knowledge via rules ...
Workflow systems—Systems that allow the representation of processes associated with the creation, use and maintenance of organisational knowledge, such as the process of creating and utilise forms and documents. Content management and document management systems—Software systems that automate the process of creating web content and/or ...
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.
One of them are expert systems, which is focused on restricted domains. [2] Expert systems are the precursor to model based systems. The main reason why model-based reasoning is researched since the 1990s is to create different layers for modeling and control of a system. [3]