Page 52 - DCAP310_INTRODUCTION_TO_ARTIFICIAL_INTELLIGENCE_AND_EXPERT_SYSTEMS

Introduction to Artificial Intelligence & Expert Systems

Notes 3.4.2 Knowledge Acquisition Problem

The preceding section provided an idealized version of how ES projects might be conducted. In
most instances, the above suggestions are considered and modified to suit the particular project.
The remainder of this section will describe a range of knowledge acquisition techniques that
have been successfully used in the development of ES.

Operational Goals

After an evaluation of the problem domain shows that an ES solution is appropriate and feasible,
then realistic goals for the project can be formulated. An ES’s operational goals should define
exactly what level of expertise its final product should be able to deliver, who the expected user
is and how the product is to be delivered. If participants do not have a shared concept of the
project’s operational goals, knowledge acquisition is hampered.

Pre-training

Pre-training the knowledge engineer about the domain can be important. In the past, knowledge
engineers have often been unfamiliar with the domain. As a result, the development process
was greatly hindered. If a knowledge engineer has limited knowledge of the problem domain,
then pre-training in the domain is very important and can significantly boost the early
development of the ES.

Knowledge Document

Once development begins on the knowledge base, the process should be well documented. In
addition to tutorial a document, a knowledge document that succinctly state the project’s current
knowledge base should be kept. Conventions should be established for the document such as
keeping the rules in quasi-English format, using standard domain jargon, giving descriptive
names to the rules and including supplementary, explanatory clauses with each rule.

!

Caution The rules should be grouped into natural subdivisions and the entire document
should be kept current.

Scenarios

An early goal of knowledge acquisition should be the development of a series of well developed
scenarios that fully describe the kinds of procedures that the expert goes through in arriving at
different solutions. If reasonably complete case studies do not exist, then one goal of pre-training
should be to become so familiar with the domain that the interviewer can compose realistic
scenarios. Anecdotal stories that can be developed into scenarios are especially useful because
they are often examples of unusual interactions at the edges of the domain. Familiarity with
several realistic scenarios can be essential to understanding the expert in early interviews and
the key to structuring later interviews. Finally, they are ultimately necessary for validation of
the system.

Interviews

Experts are usually busy people and interviews held in the expert’s work environment are
likely to be interrupted. To maximize access to the expert and minimize interruptions it can be

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