THE ROLE OF EXPERT SYSTEMS WITHIN ARTIFICIAL INTELLIGENCE
Authors: Sevda Salmanova Sevda Salmanova 
Published: November 2024

Expert systems (ES) arose as a significant practical result in the application and development of artificial intelligence methods - a set of scientific disciplines that study methods for solving problems of an intellectual (creative) nature using a computer. From the beginning of its development, the field of artificial intelligence has considered several very complex problems, which, along with others, are still the subject of research: automatic theorem proofs, machine translation, image recognition, planning, game algorithms, strategies, etc. In modern understanding, an expert system is a set of programs that perform the functions of an expert when solving problems from a certain subject area. Expert systems advise, conduct analysis, provide consultations, and diagnose. The practical use of expert systems in enterprises contributes to work efficiency and improved qualifications of specialists. When creating expert systems, several difficulties arise. This is primarily because the customer cannot always accurately formulate his requirements for the system being developed. It is also possible that difficulties of a purely psychological nature may arise when creating a knowledge base of a system, an expert may hinder the transfer of his knowledge, fearing that he will subsequently be replaced by a “machine”. But these fears are not justified, since expert systems are incapable of learning, they do not have common sense or intuition. Currently, expert systems are being developed that implement the idea of self-learning. Advantages of an ES over a human expert. Knowledge-based systems have certain advantages over human experts: they have no prejudices, they don't rush to conclusions, these systems work systematically, looking at all the details, often choosing the best alternative from all possible ones,the knowledge base can be very, very large, once entered the machine, the knowledge is stored forever, a person has a limited knowledge base, and if data is not used for a long time, then it is forgotten and lost forever. Knowledge-based systems are resistant to “interference.” The expert uses collateral knowledge and is easily influenced by external factors that are not directly related to the problem being solved. ES that are not burdened with knowledge from other areas is, by their nature, less susceptible to “noise.” Over time, knowledge-based systems may be viewed by users as a type of replication - a new way of recording and disseminating knowledge. Like other types of computer programs, they cannot replace a person in solving problems but rather resemble tools that enable him to solve problems faster and more efficiently. These systems do not replace a specialist but are a tool in his hands. The modern idea of expert systems is given in the article. Their differences from traditional software products are shown, and advantages and disadvantages are considered. A conclusion is drawn about the perspectives of development.
Keywords: information technology, expert systems, knowledge base, knowledge processing algorithm.