FREE online courses on Expert Systems - Explanations

 

One of the more interesting features of expert systems is their ability to explain themselves. Given that the system knows which rules were used during the inference process, it is possible for the system to provide those rules to the user as a means for explaining the results.

 

This type of explanation can be very dramatic for some systems such as the bird identification system. It could report that it knew the bird was a black footed albatross because it knew it was dark colored and an albatross. It could similarly justify how it knew it was an albatross.

 

At other times, however, the explanations are relatively useless to the user. This is because the rules of an expert system typically represent empirical knowledge, and not a deep understanding of the problem domain. For example a car diagnostic system has rules which relate symptoms to problems, but no rules which describe why those symptoms are related to those problems.

 

Explanations are always of extreme value to the knowledge engineer. They are the program traces for knowledge bases. By looking at explanations the knowledge engineer can see how the system is behaving, and how the rules and data are interacting. This is an invaluable diagnostic tool during development.