What are the Stages of Expert System Development?

Although great strides have been made in expediting the process of developing an expert system, it often remains an extremely time-consuming task.

It may be possible for one or two people to develop a small expert system in a few months; however, the development of a sophisticated system may require a team of several people working together for more than a year.

[button color=”red” size=”big” link=”https://namecheap.pxf.io/c/2001466/1291734/5618″ icon=”” target=”true” nofollow=”true”]Don’t miss: .COM for just $0.98![/button]

An expert system typically is developed and refined over a period of several years. We can divide the process of expert system development into five distinct stages. In practice, it may not be possible to break down the expert system development cycle precisely. However, an examination of these five stages may serve to provide us with some insight into the ways in which expert systems are developed.

Learn: What is System Analysis and What are the Stages of SDLC?

Identification

Besides we can begin to develop an expert system, it is important that we describe, with as much precision as possible, the problem that the system is intended to solve.

It is not enough simply to feel that the system would be helpful in a certain situation; we must determine the exact nature of the problem and state the precise goals that indicate exactly how we expect the expert system to contribute to the solution.

Conceptualization

Once we have formally identified the problem that an expert system is to solve, the next stage involves analyzing the problem further to ensure that its specifics, as well as it generalities, are understood.

In the conceptualization stage, the knowledge engineer frequently creates a diagram of the problem to depict graphically the relationships between the objects and processes in the problem domain.

It is often helpful at this stage to divide the problem into a series of sub-problems and to diagram both the relationships among the pieces of each sub-problem and the relationships among the various sub-problems.

Formalization

In the preceding stages, no effort has been made to relate the domain problem to the artificial intelligence technology that may solve it. During the identification and the conceptualization stages, the focus is entirely on understanding the problem.

Now, during the formalization stage, the problem is connected to its proposed solution, an expert system, by analyzing the relationships depicted in the conceptualization stage.

During formalization, it is important that the knowledge engineer be familiar with the following:The various techniques of knowledge representation and heuristic search used in expert systems.The expert system “tools” that can greatly expedite the development process. And Other expert systems that may solve similar problems and thus may be adequate to the problem at hand.

Implementation:

During the implementation stage, the formalized concepts are programmed onto the computer that has been chosen for system development, using the predetermined techniques and tools to implement a “first pass” prototype of the expert system.

Theoretically, if the methods of the previous stage have been followed with diligence and care, the implementation of the prototype should be as much an art as it is a science because following all rules does not guarantee that the system will work the first time it is implemented.

Many scientists actually consider the first prototype to be a “throw-away’ system, useful for evaluating progress but hardly a usable expert system.

Testing

Testing provides opportunities to identify the weakness in the structure and implementation of the system and to make the appropriate corrections. Depending on the types of problems encountered, the testing procedure may indicate that the system was