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In artificial intelligence (AI), an expert system is a computer system emulating the decision-making ability of a human expert. [1] Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if–then rules rather than through conventional procedural programming code. [ 2 ]
Expert systems were first developed in artificial intelligence laboratories as an attempt to understand complex human decision making. Based on positive results from these initial prototypes, the technology was adopted by the US business community (and later worldwide) in the 1980s.
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 ...
Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]
Expert systems gave us the terminology still in use today where AI systems are divided into a knowledge base, which includes facts and rules about a problem domain, and an inference engine, which applies the knowledge in the knowledge base to answer questions and solve problems in the domain. In these early systems the facts in the knowledge ...
In artificial intelligence, symbolic artificial intelligence (also known as classical artificial intelligence or logic-based artificial intelligence) [1] [2] is the term for the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of problems, logic and search. [3]
For example, Dupont created 100 expert systems, which helped them to save almost $10 million per year. [77] One of the first systems was the Pro-trader expert system that predicted the 87-point drop in the Dow Jones Industrial Average in 1986. "The major junctions of the system were to monitor premiums in the market, determine the optimum ...
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.