Introduction To Expert Systems

Introduction

An expert is a person who is well versed in a particular domain such as robotics, linguistics, medicine, finance, etc. The knowledge required for solving a given problem is called knowledge domain. A typical expert must be in a position to advise on a particular matter related to his area of expertise. He should be able to answer queries from his clients. For example, a physician should be able to answer queries such as which medicine should be given to a diseased person, what is the dosage of medicine for a particular disease, what kind of food a person suffering from diabetics should take, and so on. He need not answer queries on linguistics, robotics, or finance as these are not related to his domain. Why not a computer system does his job? The answer lies in expert system.

What are expert systems?

Expert systems are artificial intelligence programs capable of doing the functions of a typical human expert. A medical expert system, for example, should have knowledge on various kinds of patients, disorders, symptoms, medicines, etc. Knowledge base and inference engine are the two major components of an expert system. A knowledge engineer is employed to develop the required knowledge by talking to a human expert and gather as much knowledge as possible and then store it in a knowledge base. Knowledge can also be learned automatically from other sources using machine learning techniques. A user interface is used to get queries from the user. Later these queries are given to the inference engine which then makes inferences with the available rules and the knowledge base and sends the response or advice. Expert system uses an explanation facility to explain the user how it arrives at the conclusion. There are many products available in the market. MYCIN, for example, is a medical expert system and ELIZA for human-computer interaction.

Advantages and disadvantages

Computers, naturally have many advantages over human beings. For example, computers do not get exhausted, do not get fed up, work faster, do not cost more, and can work efficiently. So an expert system can obviously take these advantages for granted. On the other hand they struggle to match with humans in intelligence and commonsense. Making knowledge base on par with that of humans is a tedious job.