Transcript experts

Of
An Expert System

Introduction
 What is AI?
 Intelligent in Human & Machine?
• What is Expert System?
• How are Expert System used?
• Elements of ES
• Who are people involved in an Expert System project ?

Comparison of expert systems with
(( conventional systems and human experts ))

Knowledge
• Definition of Knowledge
• Knowledge acquisition
• Knowledge representation
 "Artificial
intelligence is the study of how to
make computers do things at which, at
moment, people are better“
Elaine Rich (1983)
 Artificial
intelligence is the branch of
computer science that focuses on the
development of computer systems.
 Artificial
is also called machine intelligence
Computer
Science

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
Expert systems are artificial intelligence (AI)
tools that capture the expertise of knowledge
workers “Experts” and provide advice to
(usually) non-experts in a given domain.
Expert systems are implemented with artificial
intelligence technology, often called expert
system shells.
Expert System Shell : is an expert system but
without knowledge “with empty knowledge”


Many expert systems are built using a generic
‘shell’. An expert system shell consists of the
programming components of an expert system
but without a KB. Using a shell, a knowledge
engineer can quickly enter a new KB and,
without the need for any programming, create a
complete working expert system.
The expert system can be used many times with
the same knowledge using that knowledge to
solve different problems (just like a doctor uses
their knowledge many times to diagnose and
cure lots of patients).
What is Knowledge ?
• Knowledge is a theoretical or practical
understanding of a subject or a domain.
• Who owns knowledge are called experts.
• Domain expert is anyone has deep knowledge
and strong practical experience in a particular
domain.
• An expert is a skilful person who can do things
other people cannot.
‘Knowledge engineering is the process of developing knowledge
based systems in any field, whether it be in the public or private
sector, in commerce or in industry’
(Debenham, 1988).

Knowledge engineering normally involves five distinct steps
(listed below) in transferring human knowledge into some form of
knowledge based system(KBS).
1. Knowledge acquisition
2. Knowledge validation
3. Knowledge representation
4. Inferencing
5. Explanation “Interface”

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Knowledge acquisition is the process of acquiring
the knowledge from human experts or other sources
(e.g. books, manuals) to solve the problem.
the knowledge acquisition process primarily
involves a discussion between the knowledge
engineer and the human expert.
A knowledge engineer can also use interviews as
method of obtaining knowledge from human experts
however they must also consider other sources of
knowledge.
(( records of past case studies , standards documentation
,knowledge from other humans who are less knowledgeable but
more available then experts. ))
 An
Interview is the easiest technique for
Knowledge Acquisition.
 To
conduct a successful interview the
knowledge engineer will need to:
•
•
•
•
plan
use appropriate stage management techniques
consider and use appropriate social skills
maintain appropriate self-control during the
interview.
 The
interview normally consists of three
parts :
Questions useful to begin the interview process include:

Can you give me an overview of the subject?
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Can you describe the last case you dealt with?
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What facts or hypotheses do you try to establish when thinking about a problem?

What kinds of things do you like to know about when you begin to think about a
problem?

Leading on to find a little more detail; tell me more about how this is achieved?

What do you do next?

How does that relate to . . . ?

How, why, when, do you do that?

Can you describe what you mean by that?
Closing an interview by reviewing the information obtained, and perhaps by alerting
the expert to the need for further interviews, is also important.

By knowledge engineer
• Tutorial interviews “presentation”
• Twenty question interviews “Yes or No”
• Teach back interviews “past interviews”
• Observation studies
 Observation of an expert doing his task
 The cooperation with the expert can be difficult
 The time consuming for the knowledge engineer

No knowledge engineer necessary
• Machine induction “ automated Knowledge Acquisition “
 Rules are automatically induced from given examples
 Database is instable & Rules are complex
 Dealing
with Multiple Experts