00ef3 es khoerul anwar
EXPERT SYSTEM
Dr. Khoerul Anwar, S.T.,M.T
STMIK Pradnya Paramita
alqhoir(at)stimata.ac.id
(c) 2017
WHAT IS EXPERT SYSTEM
Expert system is one of the sub-discipline
(Turban et al 2001) of artificial intelligence
An expert system also known as knowledge
based system is a computer program that
contains the knowledge and analytical skills
of one or more human experts in a specific
problem domain.
The goal of the design of the expert system is
to capture the knowledge of a human expert
relative to some specific domain and code
this in a computer in such a way that the
knowledge of the expert is available to a less
experienced user
CHARACTERISTIC
Expert
Non Expert
Memiliki pengetahuan
Sedikit tau tentang
{mengerti,
banyak hal
mempraktekan,
(mengetahui banyak
menjelaskan} banyak
hal, namun hanya
hal (detail) tentang
sepintas saja atau
hal khusus
dipermukaannya saja)
SPECIFIC DOMAIN
No
Fied
Expert
1
Medical
Heart
Eye
Stomach
Nerve
Pregnant
Berast cancer
etc
2
agriculture
Rice pests
3
fishery
4
computer
Network
Database
scurity
DEFINITIONS
Goodall’s (1985) : “An expert system is a
computer system that uses a
representation of human expertise in a
specialist domain in order to perform
unctions similar to those normally
performed by a human expert in that
domain”.
WHEN TO USE AN EXPERT
SYSTEM
If great costs are involved when making the decision
When applied to repetitive problem domains, the task
must be performed often
When a big difference exists between the best solution
and the worst solution
When test data is easy available to test and validate the
ES
When there is a general agreement on the system’s
conclusions. Errors in the input should be tolerated in the
system output. Experts must agree on the solutions.
When recognised expertise is available and a necessity
during the development of the ES
If the problem is clearly specifiable in the area of
expertise i.e. what the system is supposed to do before it
is done, the desired system can be developed
CONT..
If the problem is identifiable with a human expert, that is
based on human expertise. Experts must perform the task
substantially better than non-experts. The human
expertise must be scarce.
If the problem domain is well bounded: for example
defining criteria to determine the subject matter within the
system from the matter outside of the system: The task is
reasonably stable and within an acceptable narrow domain.
If solving the problem is based on knowledge rather than
common sense reasoning: ES is based on knowledge and
naïve systems on reasoning.
The solution has to be possible, justifiable and concisely
generated (using only a few hundred rules), and
The knowledge has to be of a cognitive style and
independent of common sense. Physical activities are
ruled out.
ES IN SOLVING PROBLEMS
Interpretation
Prediction
Diagnosis
Debugging
Design
Planning
Monitoring
Instruction, and
Control
ADVANTAGES OF USING
AN EXPERT SYSTEM
It improves the quality of the system
It can handle uncertainties expressed as
probabilities
It explains the logic behind its
recommendations, making the knowledge
explicit
It can be used as a training vehicle for
users who lack the expertise
It provides monetary savings once
implemented.
Experts are freed enabling them to focus on
tasks requiring their expertise
CONT…
It can codify and preserve knowledge of
the specific problem domain.
It increases programmer productivity.
It can discover new knowledge
It can provide increased output and
productivity.
It eliminates the need for expensive
equipment used by human experts for
monitoring and control
It makes knowledge and information
accessible, and
CONT…
It can outperform human experts
because of the fact that ES:
Make fewer errors
Do not become tired or bored and never
sleeps.
Will not overlook a solution
Can handle large volumes of data
Can respond more rapidly
Can function in hostile environments such as
deep-sea drillings and reactor control, and
When the knowledge of several experts is
integrated, it can outperform any one expert
ES COMPONENTS
COMPONENTS
Knowledge base :
contains
the knowledge necessary for understanding, formulating and for
solving problems.
A declarative representation of the expertise; often in IF THEN rules,
frames, logic, semantic net and case etc.
Both factual and heuristic knowledge (less rigorous, more experiental,
more judgmental knowledge of performance, rarely discused and large
individual)
Working storage :
The
data which is specific to a problem being solved
Inference engine :
the
code at the core of the system which derives recommendations from
the knowledge base and problem specific data in working storage.
Inference Engine is a brain of expert system (Here two approaches are
used i.e. forward chaining and backward chaining).
User Interface :
the
code that controls the between the user an the system
provides facilities such as menus, graphical interface etc. to make the
dialog user friendly
ROLES OF INDIVIDUALS
WHO INTERACT WITH SYSTEM
Domain expert : The individuals who
currently are experts in solving the
problems; here the system is intended to
solved
Knowledge base : the individual who the
expert’s knowledge in a declarative form
that can be used by the expert system
User : the individual who will be
consuliting the system to get advise
which would have been provided by the
expert.
ES LIFE CYCLE
CHARACTERISTICS OF AN
EXPERT SYSTEM
Expert system provides the highquality performance which solves
difficult programs in a domain as good
as or better than human experts.
Expert System possesses vast
quantities of domain specific
knowledge to the minute details.
Expert systems apply heuristics to
guide the reasoning and thus reduce
the search area for a solution.
CONT..
A unique feature of an expert system
is its explanation capability. It
enables the expert system to review
its own reasoning and explain its
decisions.
Expert systems employ symbolic
reasoning when solving a problem.
Symbols are used to represent
different types of knowledge such as
facts, oncepts and rules.
Expert system can advice, modifies,
update, expand & deals with
Dr. Khoerul Anwar, S.T.,M.T
STMIK Pradnya Paramita
alqhoir(at)stimata.ac.id
(c) 2017
WHAT IS EXPERT SYSTEM
Expert system is one of the sub-discipline
(Turban et al 2001) of artificial intelligence
An expert system also known as knowledge
based system is a computer program that
contains the knowledge and analytical skills
of one or more human experts in a specific
problem domain.
The goal of the design of the expert system is
to capture the knowledge of a human expert
relative to some specific domain and code
this in a computer in such a way that the
knowledge of the expert is available to a less
experienced user
CHARACTERISTIC
Expert
Non Expert
Memiliki pengetahuan
Sedikit tau tentang
{mengerti,
banyak hal
mempraktekan,
(mengetahui banyak
menjelaskan} banyak
hal, namun hanya
hal (detail) tentang
sepintas saja atau
hal khusus
dipermukaannya saja)
SPECIFIC DOMAIN
No
Fied
Expert
1
Medical
Heart
Eye
Stomach
Nerve
Pregnant
Berast cancer
etc
2
agriculture
Rice pests
3
fishery
4
computer
Network
Database
scurity
DEFINITIONS
Goodall’s (1985) : “An expert system is a
computer system that uses a
representation of human expertise in a
specialist domain in order to perform
unctions similar to those normally
performed by a human expert in that
domain”.
WHEN TO USE AN EXPERT
SYSTEM
If great costs are involved when making the decision
When applied to repetitive problem domains, the task
must be performed often
When a big difference exists between the best solution
and the worst solution
When test data is easy available to test and validate the
ES
When there is a general agreement on the system’s
conclusions. Errors in the input should be tolerated in the
system output. Experts must agree on the solutions.
When recognised expertise is available and a necessity
during the development of the ES
If the problem is clearly specifiable in the area of
expertise i.e. what the system is supposed to do before it
is done, the desired system can be developed
CONT..
If the problem is identifiable with a human expert, that is
based on human expertise. Experts must perform the task
substantially better than non-experts. The human
expertise must be scarce.
If the problem domain is well bounded: for example
defining criteria to determine the subject matter within the
system from the matter outside of the system: The task is
reasonably stable and within an acceptable narrow domain.
If solving the problem is based on knowledge rather than
common sense reasoning: ES is based on knowledge and
naïve systems on reasoning.
The solution has to be possible, justifiable and concisely
generated (using only a few hundred rules), and
The knowledge has to be of a cognitive style and
independent of common sense. Physical activities are
ruled out.
ES IN SOLVING PROBLEMS
Interpretation
Prediction
Diagnosis
Debugging
Design
Planning
Monitoring
Instruction, and
Control
ADVANTAGES OF USING
AN EXPERT SYSTEM
It improves the quality of the system
It can handle uncertainties expressed as
probabilities
It explains the logic behind its
recommendations, making the knowledge
explicit
It can be used as a training vehicle for
users who lack the expertise
It provides monetary savings once
implemented.
Experts are freed enabling them to focus on
tasks requiring their expertise
CONT…
It can codify and preserve knowledge of
the specific problem domain.
It increases programmer productivity.
It can discover new knowledge
It can provide increased output and
productivity.
It eliminates the need for expensive
equipment used by human experts for
monitoring and control
It makes knowledge and information
accessible, and
CONT…
It can outperform human experts
because of the fact that ES:
Make fewer errors
Do not become tired or bored and never
sleeps.
Will not overlook a solution
Can handle large volumes of data
Can respond more rapidly
Can function in hostile environments such as
deep-sea drillings and reactor control, and
When the knowledge of several experts is
integrated, it can outperform any one expert
ES COMPONENTS
COMPONENTS
Knowledge base :
contains
the knowledge necessary for understanding, formulating and for
solving problems.
A declarative representation of the expertise; often in IF THEN rules,
frames, logic, semantic net and case etc.
Both factual and heuristic knowledge (less rigorous, more experiental,
more judgmental knowledge of performance, rarely discused and large
individual)
Working storage :
The
data which is specific to a problem being solved
Inference engine :
the
code at the core of the system which derives recommendations from
the knowledge base and problem specific data in working storage.
Inference Engine is a brain of expert system (Here two approaches are
used i.e. forward chaining and backward chaining).
User Interface :
the
code that controls the between the user an the system
provides facilities such as menus, graphical interface etc. to make the
dialog user friendly
ROLES OF INDIVIDUALS
WHO INTERACT WITH SYSTEM
Domain expert : The individuals who
currently are experts in solving the
problems; here the system is intended to
solved
Knowledge base : the individual who the
expert’s knowledge in a declarative form
that can be used by the expert system
User : the individual who will be
consuliting the system to get advise
which would have been provided by the
expert.
ES LIFE CYCLE
CHARACTERISTICS OF AN
EXPERT SYSTEM
Expert system provides the highquality performance which solves
difficult programs in a domain as good
as or better than human experts.
Expert System possesses vast
quantities of domain specific
knowledge to the minute details.
Expert systems apply heuristics to
guide the reasoning and thus reduce
the search area for a solution.
CONT..
A unique feature of an expert system
is its explanation capability. It
enables the expert system to review
its own reasoning and explain its
decisions.
Expert systems employ symbolic
reasoning when solving a problem.
Symbols are used to represent
different types of knowledge such as
facts, oncepts and rules.
Expert system can advice, modifies,
update, expand & deals with