Expert Systems are used in all sectors of organizations to help aid users with their work

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Expert Systems

Amirah Nosimohomed

 Business Information Technology, Swansea Institute of Higher Education

ABSTRACT

Expert systems are used in all sectors of organizations to help aid users with their work. This paper will be giving a brief introduction to expert systems and will be looking back at the history of expert systems. This paper will also look at the characteristics of expert systems and what they are used for. The advantages and disadvantages of expert systems will also be discussed in this paper.

Keywords: Expert Systems, Artificial Intelligence, knowledge based systems, decision support systems

[1] Introduction

Expert systems are programs that provide the type of advice that would be expected from a human expert. It is also known as a knowledge based system. Expert systems are able to store and manipulate knowledge so that they can help a user solve a problem or make a decision.

Expert systems technology derives from the research discipline of Artificial Intelligence (AI): It is said by Jackson (1998, pg2) “Artificial Intelligence is a branch of computer science concerned with the design and implementation of programs which are capable of emulating human cognitive skills such as problem solving, visual perception and language understanding”

The main features of expert systems are that it is it is limited to a specific domain; it is typically rule based which means that users of the expert system will have to type commands and rules for the expert system to respond. It can also reason with certain data, for example if the expert system thinks that the data given is incorrect it can query the data and information that it has been given. It delivers advice, for example an expert system can give advice to a surgeon about the best method in carrying out complicated operations.  

Typical tasks for and expert system involve; The interpretation of data such as solar signals, diagnosis of malfunction such as equipment faults or human diseases, structural analysis of complex objects such as chemical compounds, configuration of complex objects such as computer systems, planning of sequences of actions such as what might be performed by robots.

Generally speaking an expert systems overall performance depends on the knowledge it can bring to bear on a problem to be solved. The quality of internal data processing in turn depends upon knowledge acquisition, knowledge representation and reasoning strategy. Performance also depends upon the quality of data input.

One of the most powerful attributes of expert systems is the ability to explain reasoning. Since the system remembers its logical chain of reasoning, a user may ask for an explanation of a recommendation and the system will display the factors it considered in providing a particular recommendation. This attribute enhances user confidence in the recommendation and acceptance of the expert system. (Giarratano et al, 2000)

[2] History of Expert Systems

Dendral was the earliest known expert system, which was built in 1965. It was developed by Edward Feigenbaum; it was used for scientific reasoning in organic chemistry. It took over a decade to gather information from relevant chemists, genetics and computers scientists.

Then MACSYMA, was designed in 1968 by Carl Engleman, William Martin and Joel Moses. It was a large interactive mathematics expert system used by MIT to manipulate mathematical expressions symbolically. It had a very powerful problem-solving program with the capability of performing over 600 distinct mathematical operations. It then evolved into a widely used commercial product.

Then in 1972 came MYCIN, which was the work of Edward Shortliffe. It was the best known medical system. It was a program used for advising physicians on diagnosing and treating bacterial infections of the blood and also for treating meningitis. It conducts a question an answer dialog. INTERNIST, which was another medical diagnosis tool that contained nearly 100,000 relationships between symptoms and diseases. It proved to be very efficient for doctors around the world as they were able to diagnose patients quickly and therefore treating them quickly as well. It was also know as the quick medical reference (QMR).

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An expert system was also built for geologists, which was called Prospector and was made in 1979 to help aid geologists in their search for ore deposits. It became famous when it analysed geological data from a site near Mount Tolman in eastern Washington and predicted the existence of molybdenum.

XCON was the first system employed in the industrial world. It decided what components were needed in order to assemble a complete computer system. It outputted this information as a set of diagrams to technicians who physically assemble the computer system.

In 1986 Companies such as DuPont, General Motors, ...

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