Introduction
By reading the title , you might think : “Wait a minute. Is there any Stupid SW?”. Please don’t think that, the idea of the post is to show you that there is type of software which aims to emulate Human Intelligence.
When it is time to build Intelligent SW?
Not all problems look alike. There are some problems that can be solved by implementing a set of steps. These kind of problems have an algorithmic solution. On the other hand we have problems that can’t be solve by an algorithmic solution. These are the ones that need Intelligent SW to solve them.
There is more than one Intelligent SW that can be build. Some of them are listed in the table below.
|
INTELLIGENT SOFTWARE |
TYPE OF PROBLEM |
| Expert Systems (With knowledge Base) | Problem that requires human expertise. |
| Genetic Algorithms | Optimization problems |
| Artificial Neuronal Network | Pattern recognition |
From all these, I will choose the Expert System to compare with the Traditional Software.
Comparison between Traditional SW and Expert Systems
| Traditional SW | Expert System | |
| Data | Objects, variables, Constants | Rules and Facts |
| Elements | Programs and Data | Rules, Facts and Inference |
| Engineering Area related to the build of them. | Software Engineering | Knowledge Engineering |
| SW Life Cycles based on | Spiral Model | IDEAL Methodology |
Some aspects need to be explained. The IDEAL methodology is based on the Spiral Model of the Software Engineering. With the difference that the IDEAL methodology considers the corrective maintenance of the knowledge base.
Another thing to keep in mind is that SW Engineering and the Knowledge Engineering complement with each other. Usually an Expert System is a module of a Software Engineering project.
Conclusion
- Not all problems can be solved by an algorithmic solution.
-SW Engineering and the Knowledge Engineering can live together.
