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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 are a crucial subset of artificial intelligence (AI) that simulate the decision-making ability of a human expert. These systems use a knowledge base filled with domain-specific information and rules to interpret and solve complex problems.
An expert system is a computer program that uses artificial intelligence (AI) technologies to simulate the judgment and behavior of a human or an organization that has expertise and experience in a particular field. Expert systems are usually intended to complement, not replace, human experts.
Expert Systems papers deal with all aspects of knowledge engineering: Artificial Intelligence, Software and Requirements Engineering, Human-Computer Interaction, individual methods, techniques in knowledge acquisition and representation, application and evaluation and construction of systems.
Expert systems are a branch of artificial intelligence that aim to provide computerized decision-making capabilities similar to those of a human expert in a specific domain. They are designed to solve complex problems using a set of rules or algorithms that can mimic human reasoning processes.
Expert system, a computer program that uses artificial-intelligence methods to solve problems within a specialized domain that ordinarily requires human expertise. The first expert system was developed in 1965 by Edward Feigenbaum and Joshua Lederberg of Stanford University in California, U.S.
A computer program that simulates the judgment of a human expert is known as an expert system in ai. A few examples of an expert system are DENDRAL, a molecular structure prediction tool for chemical analysis.