Page 182 - DCAP506_ARTIFICIAL_INTELLIGENCE

Artificial Intelligence

Notes certainty measures) based on this data. In a simple forward chaining rule-based system the case
specific data will be the elements in working memory.

Figure 13.2: Important Module of ES

Almost all expert systems also have an explanation subsystem, which allows the program to
explain its reasoning to the user. Some systems also have a knowledge base editor which help
the expert or knowledge engineer to easily update and check the knowledge base.
One important feature of expert systems is the way they (usually) separate domain specific
knowledge from more general purpose reasoning and representation techniques. The general
purpose bit (in the dotted box in the figure) is referred to as an expert system shell. As we see in the
Figure 13.2, the shell will provide the inference engine (and knowledge representation scheme),
a user interface, an explanation system and sometimes a knowledge base editor. Given a new
kind of problem to solve (say, car design), we can usually find a shell that provides the right sort
of support for that problem, so all we need to do is provide the expert knowledge. There are
numerous commercial expert system shells, each one appropriate for a slightly different range
of problems.

Did u know? Expert systems work in industry includes both writing expert system shells
and writing expert systems using shells.

Notes Using shells to write expert systems generally greatly reduces the cost and time of
development (compared with writing the expert system from scratch).

The following general points about expert systems and their architecture have been illustrated:
1. The sequence of steps taken to reach a conclusion is dynamically synthesized with each
new case. It is not explicitly programmed when the system is built.
2. Expert systems can process multiple values for any problem parameter. This permits
more than one line of reasoning to be pursued and the results of incomplete (not fully
determined) reasoning to be presented.
3. Problem solving is accomplished by applying specific knowledge rather than specific
technique. This is a key idea in expert systems technology. It reflects the belief that human
experts do not process their knowledge differently from others, but they do possess different
knowledge. With this philosophy, when one finds that their expert system does not produce
the desired results, work begins to expand the knowledge base, not to reprogram the
procedures.

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