At the moment we decide to start building an Expert System, there are many elements to take into consideration. But in this new post we’ll take special attention to the interaction between the Human Expert, the Knowledge Engineer and the Knowledge Base of the Expert System.
The expert’s knowledge about solving specific problems is called knowledge domain of the expert.
For example,a medical expert system designed to diagnose infectious diseases will have a great deal of knowledge about certain symptoms caused by infectious diseases. In this case, the deal of knowledge domain is medicine and consists on knowledge about diseases, symptoms, and treatments.
The next schema shows the relationship between the problem and the knowledge domain:
HUMAN EXPERT, KNOWLEDGE ENGINEER AND THE KNOWLEDGE
A Human Expert, as we defined in the previous post, is a person who has expertise in a certain area, this expert can solve problems that most people cannot solve or can solve them much more efficiently. The role of the Knowledge Engineer is to “translate” and filter all the information of the human expert, and put all the obtained knowledge in to the Knowledge Base (represented by rules commonly).
The next schema shows the process of how to build the knowledge base in an expert system:
-If the human expert can’t explain how a problem is solved, it’s not possible to encode the knowledge in an expert system based on explicit knowledge.
-A human expert has expertise in a certain area, not necessarily an expert in biology is going to be an expert in cooking pizza.
-The Knowledge Engineer usually doesn’t know technical terms of the expert, so the human expert should express his knowledge using simple and understandable terms.
-Expert systems increase confidence that the correct decision was made by providing a second opinion to a human expert or break a tie in case of disagreements by multiple human experts (An expert System can’t feel stress or be tired as a human expert).