Information Technology Reference
In-Depth Information
The Inference Engine
The overall purpose of an
inference engine
is to seek information and relationships from the
knowledge base and to provide answers, predictions, and suggestions similar to the way a
human expert would. In other words, the inference engine is the component that delivers
the expert advice. To provide answers and give advice, expert systems can use backward and
forward chaining.
Backward chaining
is the process of starting with conclusions and working
backward to the supporting facts. If the facts do not support the conclusion, another con-
clusion is selected and tested. This process is continued until the correct conclusion is
identified.
Forward chaining
starts with the facts and works forward to the conclusions.
Consider the expert system that forecasts future sales for a product. Forward chaining starts
with a fact such as “The demand for the product last month was 20,000 units.” With the
forward-chaining approach, the expert system searches for rules that contain a reference to
product demand. For example, “IF product demand is over 15,000 units, THEN check the
demand for competing products.” As a result of this process, the expert system might use
information on the demand for competitive products. Next, after searching additional rules,
the expert system might use information on personal income or national inflation rates. This
process continues until the expert system can reach a conclusion using the data supplied by
the user and the rules that apply in the knowledge base.
inference engine
Part of the expert system that seeks
information and relationships from
the knowledge base and provides
answers, predictions, and
suggestions similar to the way a
human expert would.
backward chaining
The process of starting with
conclusions and working backward
to the supporting facts.
forward chaining
The process of starting with the
facts and working forward to the
conclusions.
The Explanation Facility
An important part of an expert system is the
explanation facility
, which allows a user or
decision maker to understand how the expert system arrived at certain conclusions or results.
A medical expert system, for example, might reach the conclusion that a patient has a defective
heart valve given certain symptoms and the results of tests on the patient. The explanation
facility allows a doctor to find out the logic or rationale of the diagnosis made by the expert
system. The expert system, using the explanation facility, can indicate all the facts and rules
that were used in reaching the conclusion. This facility allows doctors to determine whether
the expert system is processing the data and information correctly and logically.
explanation facility
Component of an expert system that
allows a user or decision maker to
understand how the expert system
arrived at certain conclusions or
results.
The Knowledge Acquisition Facility
A difficult task in developing an expert system is the process of creating and updating the
knowledge base. In the past, when more traditional programming languages were used,
developing a knowledge base was tedious and time consuming. Each fact, relationship, and
rule had to be programmed into the knowledge base. In most cases, an experienced pro-
grammer had to create and update the knowledge base.
Today, specialized software allows users and decision makers to create and modify their
own knowledge bases through the knowledge acquisition facility (see Figure 11.11). The
purpose of the
knowledge acquisition facility
is to provide a convenient and efficient means
for capturing and storing all components of the knowledge base. Knowledge acquisition
software can present users and decision makers with easy-to-use menus. After entering the
appropriate attributes, the knowledge acquisition facility correctly stores information and
relationships in the knowledge base, making the knowledge base easier and less expensive to
set up and maintain. Knowledge acquisition can be a manual process or a mixture of manual
and automated procedures. Regardless of how the knowledge is acquired, the knowledge base
must be validated and updated frequently to make sure that it is still accurate.
knowledge acquisition facility
Part of the expert system that
provides convenient and efficient
means of capturing and storing all
the components of the knowledge
base.
Figure 11.11
Knowledge Acquisition Facility
The knowledge acquisition facility
acts as an interface between experts
and the knowledge base.
Knowledge
acquisition
facility
Knowledge base
Expert
