Understanding Expert Systems

Over the years, it has been verified that some problems such as information processing for facial or voice recognition, systems with a high degree of complexity, among others, can be solved by computer solutions, specifically, Intelligence Artificial (IA), which is responsible for studying these problems that at first glance are impossible and difficult to formulate using computers. Currently, various branches of this science are derived, among them are the expert systems , which has been used by the industry to greatly improve its production processes.

But what are Expert systems?

An expert system can be defined as a computer system which is made up of hardware and software, which have the ability to simulate human experts, in a certain area of specialization. Durkin (1994)

Generally speaking, an expert system is like a consultant, who, using his skills, helps people in decision-making. This is why a large number of applications have emerged that use expert systems to automate certain systems, seeking to help people and organizations in different sectors. Some applications where they have already been used and with great success are:

  • Bank transactions through ATMs and the Internet.
  • Traffic control with the help of traffic lights.
  • Medical diagnosis.
  • Supervision of the operation of the plant and the controller, etc.

The current designs of expert systems comprise five plugins, including: A Knowledge Base: contains the knowledge in a particular domain, as well as the rules for solving a problem, procedures and data intrinsic relevant to the domain. Inference Engine: Its function is to obtain the relevant knowledge from the knowledge base, interpret it and find a relevant solution for the user’s problem. Learning Module: allows the expert system to acquire more and more knowledge from various sources and store it in the knowledge base. User Interface: This module makes it possible for a non-expert user to interact with the expert system and find a solution to a problem, and finally. Explanation module: in this module the expert system gives an explanation to the user on how the expert system came to a particular conclusion. In this way, he argues the results presented with the greatest accuracy.

So why use expert systems?

There are several compelling reasons that explain why using expert systems has its advantages, for example: An expert system allows a complex problem to be solved by people with little experience in the subject, its response time is shorter than that of a human expert, since he can solve problems and answer questions in a short time and this leads to the economic savings required for the solution of a certain problem, having an updated knowledge base that comes from different sources of information, being a competitive advantage when making decisions that make a difference.

Therefore, an expert system takes facts and heuristics to solve complex decision-making problems. In that order, improved decision quality, cost reduction, consistency, reliability, speed are the key benefits of an expert system.

However, it must be taken into account that an expert system cannot provide creative solutions and its maintenance can be expensive. Other than that, its applications are very wide and are very useful to ensure fast and accurate