EXPERT SYSTEMS

Expert Systems



Expert Systems

Introduction

Expert systems are essentially the computer programs, which base on artificial intelligence technologies. These systems have got wide popularity during the last 10 years. Many business organizations rely on expert systems for decision making processes, as this system significantly emulates the decision making capability of human experts. This paper explains the expert systems, and provides few recent example of its use in various areas such as process control, traffic light monitoring, car maintenance and troubleshooting, E-learning and academic advice.

Discussion

An expert system is a computer program that solves the problem in any field depending on the stored knowledge. The way of problem solving is much the same as of human expert. This knowledge essentially comes from the conversations between the expert system's developer and experts of the field. The system afterwards uses this knowledge to answer the queries of users. The next section briefly describes the working of an expert system.

Working of Expert System

The expert system relies on the knowledge of facts, the relation between these facts, and methods for accessing the stored facts. Knowledge engineer is a person who is responsible for creating and managing the knowledge efficiently in the knowledge base (Tzafestas S.G., 2011).

Figure 1 shows the basic architecture of the exert system, along with interlinks between various components of the system.

Figure 1: Architecture of Expert System

The main components of expert system include Knowledge Base (KB), Data Base (DB), inference engine, User Interface (UI), Explanation Component (EC), Work Space (WS), and Knowledge Acquisition (KA) component.

The knowledge base stores the knowledge including facts and rules; the difference between facts and rules occur later in this section. The Database stores the numerical values and the inference engine provides the method for accessing the knowledge of the knowledge base. The supplementary components of the system such as explanation component and user interface provide the means to the user for interacting with the expert system. The role of explanation system is to inform the user, that how the expert system has come out with definite conclusions, while the work space the physical memory location where the expert systems stores the description of the problem based on the information supplied by the user, or inferred from the knowledge base. Finally, the knowledge acquisition component extracts the knowledge from the expert system.

Also, the working of expert systems typically depend on the internal arrangement of expertise in the expert system. The knowledge arranges in the following ways.

a) Rules based

In this type, the knowledge comes out from the expert systems using two building blocks; namely, the knowledge base and the inference engine.

The knowledge base contains all the knowledge of the expert system in the form of rules. Typical expert systems may have few thousand rules in its knowledge base. These rules support the expert systems in problem solving process, by providing strategies, directives and conclusions.

The rules bases on the if-then-else structure, i.e., if any condition comes to be true, perform any ...