ExpertSystems

Information and Communication Technology
Expert systems
 ICT systems that use artificial intelligence to
make decisions based on data supplied in
the form of answers to questions.
 This means that the system is able to
respond in the way that a human expert in
the field would to come to a conclusion.
 A good expert system is one that can match
the performance of a human expert in the
field.
By/ Eng. Mohamed Omar @ Alrowad International School2

The four component of an expert
system
Expert systems consist of the following
components:

system
Knowledge base – a huge
organised set of knowledge about particular
subject.
 It contains facts and also judgmental
knowledge, which gives it the ability to
make a good guess, like a human expert.

system
 Rule base – is a set of rules which will
be used by an inference engine together with
the data or facts in the knowledge base, to
reason through a problem.
 Consequently, a different problem can be
solved with the same expert system using the
knowledge that is appropriate.
 In addition the system explains the logical
reasoning that it has used to come to its
conclusions.

system
 Inference engine – a set of rules on
which to base decisions.
 Most of these rules have the ‘if-the’ structure.
 It is the part of the expert system that does the
reasoning by manipulating and using the
knowledge in the knowledge base.
 There is usually a way of phrasing a question to
the system or a way of searching for
information using a search engine.

system
 User Interface – the user
interface presents questions and
information to the operator.
 It also receives answers from the operator

Creating a new expert system
Here are the steps taken
when creating a new expert
system:

Potential users of the system are
interviewed to find out what is
required from the desired expert
system.
Experts are consulted and asked to
supply data about their expertise.
The knowledge base is created using
the information collected from the
experts.
Rules connecting the knowledge are
identified.

The rules are used to create the
inference engine.
The user interface is created which
allows the user to enter data as input
from various sources. The output
screens are also created.
Testing is undertaken to ensure that the
expert system is producing the same
results as a human expert in the field.
The system is evaluated and
improvements are made to the system
before it goes live.

Why and where expert systems
are used
Expert systems can be used
for all sorts of applications
and here are some of them:

Medical diagnosis
 There are many types of blood infections.
 If the correct antibiotic is given, the infection
will clear up.
 The trouble is matching the correct
antibiotic to the infection
 This is where the expert system can be
used by a less experienced doctor to make
a correct diagnosis without having to waste
time growing a culture, which could take
several days, by which time the patient
could be dead.

Prospecting for minerals and oil
 Using geological information, an expert
system can use the information to
determine the most likely places to choose
for further exploration.
 This reduces the cost of mineral or oil
exploration because highly paid and very
experienced geologists do not need to be
paid to interpret the data as the expert
system can do this.

Car engine fault diagnosis
 Modern car engines are very complex and
when they go wrong it is hard for engineers
to know what the problem is.
 Using an expert system created by the car
manufacturer, the engineers can be guided
through a series of tests until the exact fault
is identified.

For giving Tax advice to individuals
and companies
 Tax is complex and a lot of expertise is
needed in order to give the correct advice.
 This is where expert systems come in.
 They are able to store a huge amount of
data and they can ask the user a series of
questions and come up with expert advice
on how to pay less tax.

Other applications used
 Insurance planning
 Plant and animal identification
 Route scheduling for delivery vehicles
 Financial planning
 Investment analysis
 Credit analysis
 Chess game

Advantages of expert systems
 Always ask a question that a human expert may forget
to ask.
 Cheaper – it is cheaper to use an expert system than a
human expert because a human experts demand high
wages.
 Fewer mistakes – human experts may forget but expert
systems do not.
 More expertise than a single expert – many experts
can be used to create the data and the rules, so the
expert system is a result of not one but many experts.

Disadvantages of expert systems
 They lack common sense – humans have
common sense, so they are able to decide
whether an answer is sensible or ridiculous.
 Human experts can make judgments based
on their life experiences, and not just on a
limited set of rules, as is the case with
computer systems.

Disadvantages of expert systems
 The system relies on the rules being correct –
mistakes could be made that make the system
inaccurate.
 The users (mechanics/doctors/patients) will
need training in how to use it, which takes time
and money.
 It will need continually updating which can take
it temporarily out of use.

ExpertSystems

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