Expertensystem

Expertensystem, also known as an expert system, is a computer program that emulates the problem-solving ability of human experts in a defined domain. It typically consists of a knowledge base that stores domain knowledge, an inference engine that applies rules to solve problems, and a user interface for interaction and a mechanism to explain its conclusions. Knowledge bases may use if-then rules, frames, or object models, often augmented with a glossary of domain terms.

Expert systems emerged in the 1970s and 1980s as a major strand of symbolic artificial intelligence. Early and influential systems include MYCIN for medical diagnosis and treatment advice, DENDRAL for chemical structure elucidation, and XCON for configuring computer systems. They are deployed in fields where expert knowledge is critical and must be consistently applied, such as medical decision support, fault diagnosis, product configuration, and process optimization.

Strengths include capturing specialist knowledge, offering consistent reasoning, and providing explanations that justify conclusions. They can deliver rapid, rule-based problem solving and support human decision makers. Limitations involve brittleness when the knowledge base does not cover new situations, high costs of knowledge elicitation and maintenance, and limited learning capability unless integrated with data-driven methods. Handling uncertainty has traditionally relied on approximate reasoning techniques, which may oversimplify real-world ambiguity.

Today, expert systems are often used in hybrid form, combining symbolic reasoning with machine learning, and are featured in regulated industries where traceability and explainability are important. They remain relevant for codifying expert expertise and supporting decision making, even as newer AI approaches develop.