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T o p ic                X       Expert
                                         System
               8
     LEARNING OUTCOMES
    By the end of this topic, you should be able to:
    1.    Describe what an Expert System is and its applications;
    2.    Describe the steps involved in producing rules and information
          gathering;
    3.    List the 11 main characteristics of an Expert System; and
    4.    Differentiate between conventional information systems and the
          Expert System.


X        INTRODUCTION
In this topic, you will learn about one of the branches of artificial intelligence,
which is the Expert System. The Expert System is also known as the knowledge-
based System. The Expert System comprises many types of Systems based on
rules, frames and fuzzy sets. In this topic, you will also be exposed to the most
popular expert system, the System based on rules.

 Definition
 Expert System is an information system that is capable of mimicking human
 thinking and making considerations during the process of decision-making.


It is an information system that has been used to solve a problem that usually
requires an expert to solve.
TOPIC 8    EXPERT SYSTEM    W    153



 8.1       WHAT IS AN EXPERT SYSTEM?

         SELF-CHECK 8.1

     Currently, the Expert System is a popular topic in the Management
     Information System. In your own words, explain what is an Expert
     System.



According to Efraim Turban (2001), the Expert System comes from the
Knowledge-Based Expert System terminology. Expert System (ES) is a System
that uses human knowledge stored inside a computer to solve problems that
requires human expertise to solve. A good ES is a system that can copy the
process of reasoning in a human.

What is meant by an expert? An expert is a person that has the expertise and
knowledge of his specialised field. Examples of experts are a heart specialist and
a mathematics expert. Through experience, an expert expands his skills to enable
him to solve problems heuristically, efficiently and effectively.


8.1.1      Expert System Definition
Prof. Edward Feigenbaum (1983, p.?) from Stanford University, a famous
researcher on ES defines ES as:

   "«an intelligent computer programme that uses knowledge and
   reasoning procedures to solve difficult problems that need certain
   expertise to solve the problems."

ES is developed to model the ability of an expertise in solving problems. In the
process of modelling the method which an expert uses to solve a problem, ES
must be able to provide users with the services and facilities that an expert can
usually provide.


8.1.2      Why is an Expert System Needed?
You must be thinking of the rationale behind the process of transferring the
knowledge of an expert to a computer. Table 8.1 will answer your query by
comparing the Expert System to that of humans.
154          X TOPIC 8     EXPERT SYSTEM



        Table 8.1: Comparisons between an Expert System and that of a Human Expert

               Factor                     Human Expert            Expert System
    Time (can be obtained)        Working days only        Anytime
    Geography                     Local                    Anywhere
    Safety                        Cannot be replaced       Can be replaced
    Damages                       Yes                      No
    Speed and Efficiency          Changes                  Consistent
    Cost                          High                     Intermediate

An Expert System is built because of two factors: either to replace or to help an
expert.

Some of the reasons for the need of an Expert System to replace an expert are:
x      To enable the use of expertise after working hours or at different locations.
x     To automate a routine task that reqquires human expertise all the time
      unattended, thus reducing operational costs.
x     To replace a retiring or an leaving employee who is an expert.
x     To hire an expert is costly.


             ACTIVITY 8.1

        Has your car ever broken down? Think about how an Expert system
        can help a car owner. Discuss this with your course mates.



The Expert System is used to:
x     Help experts in their routine to improve productivity.
x     Help experts in some of their more complex and difficult tasks so that the
      problem can be managed effectively.
x     Help an expert to obtain information needed by other experts who have
      forgotten about it or who are too busy to search for it.
TOPIC 8     EXPERT SYSTEM     W   155



8.1.3      Expert System Application
Expert System is widely used in all types of fields and sectors like medicine,
engineering, education, marketing, tax planning and more. We will study several
other applications in the financial, production and military sectors.

x   Banking and Financial sector ă Application of EIS

    System used:
    -   An Expert System that helps bank managers in making decisions on
        granting loans.
    -   An Expert System that advises bank managers in giving housing loans.
    -   An Expert System that advises insurance companies on the risks involved
        in insuring a customer or a company.
    -   An Expert System that helps banks decide on whether a customer is
        entitled for a credit card or not.
    -   An Expert System that identifies computer fraud and controls it.

x   Production industries and Military ă Application of EIS

    Type of Expert System used:
    -   An Expert System capable of diagnosing some technical malfunctions in
        airplanes, gas turbines and helicopters.
    -   An Expert System that helps identify threats that may put security at risk.
    -   An Expert System that helps form and produce small mechanical items.
156     X TOPIC 8      EXPERT SYSTEM




            SELF-CHECK 8.2
      Differentiate between human expertise and the Expert system:


                  Factor                Human Expertise               Expert System
       Time (which         can   be
       obtained)
       Geography
       Security
       Malfunctions
       Performance and speed
       Cost



                            Table 8.2: Problem-Solving Paradigm

 Problem-Solving Paradigm                 Example of Expert System application

Control                          Controlling the Behaviour of the system according to
                                 specification.

Design                           Aligning objects following limits.

Diagnosis                        Providing reasons for system malfunction based on
                                 observation.

Instruction                      Diagnosing and improving behaviour of students.

Translation                      Providing reasons for situations based on data given.

Assessment                       Comparing observation data with expectations.

Planning                         Designing a plan of action.

Prediction                       Providing reasons on the cause and effect of a certain
                                 decision based on situation.

Selection                        Identifying the best selection from all alternatives and
                                 probabilities.

Prescription                     Suggesting solution to improve a malfunction system.
TOPIC 8    EXPERT SYSTEM    W    157



Table 8.2 lists ten (10) paradigms in problem-solving that an Expert System is
capable of solving.


8.2          KNOWLEDGE
           SELF-CHECK 8.3
       Knowledge helps humans solve problems. How is knowledge used in
       a system?


Around the 1970s, computer scientists accepted the fact that in order to enable a
machine to solve intellectual problems, a machine must know how to first solve
it. In other words, it had to have the 'how-to' knowledge to solve problems in a
specific domain.

x     What is knowledge?

    Definition
    Knowledge is a theoretical or practical understanding of a subject or domain.



      Knowledge is a combination and mix of information that is already known,
      and knowledge is power. Anyone who has a certain amount of knowledge
      may be considered an expert. Experts are people who have power in the
      organisation. In any successful company, there are a certain number of first
      class experts and the companies will not succeed without them. As an
      example, Sun Microsystem has James Gosling, the founder of Java
      programming.

x     Who is fit to be called an expert?
      Anyone can be called an expert as long as that person has a vast knowledge
      of the particular field and has practical experience in a certain domain.
      However, the person is restricted to his or her own domain. For example,
      being an IT expert does not mean that the person is an expert in all IT
      domains but she may be an expert in intelligence systems or an expert in only
      the development of an intelligence agent.
158     X TOPIC 8    EXPERT SYSTEM




x   How does an expert think?
    The human mental process is too complex and complicated to be drafted as
    an algorithm. Many experts can only create rules in solving certain problems.
    We will learn more about the steps in referencing the knowledge acquired
    from an expert with the rules when we learn about the basic architecture of
    an Expert System. On the other hand, Figure 8.1 and 8.2 below show the
    different ÂthinkingÊ of an expert and a machine.


        Knowledge Domain Long-
             term Memory
                                                                     Advisor:
                                                                     Conclusion
                                                                     based on
      Short-term Memory                                              Cases/Facts
      Conclusion Result
      Facts/Cases Reasoning


               Figure 8.1: Human problem-solving architectural structure



         Knowledge Database
          Domain Knowledge
                                                                       User:
                                                                       Conclusion
                                                                       based on
      Working Memory                                                   Cases/Facts
      Conclusion
      Reasoning Facts/Cases




          Figure 8.2: An expert system problem-solving architectural structure


          SELF-CHECK 8.4

       Write down the differences between the human problem-solving
       architecture and those of the Expert System.
TOPIC 8     EXPERT SYSTEM   W   159



    8.3     EXPERT SYSTEM ARCHITECTURE




                    Figure 8.3: Basic components of an Expert System


An ES merges knowledge, facts and reasoning techniques in producing a
decision. In order to produce a decision, an ES fundamental architecture is
required, as shown in Figure 8.3. The components are:
x    Knowledge base
x    Inference engine
x    Explanation facility
x    Knowledge acquisition facility


8.3.1       Knowledge Base
A knowledge database stores two important things: facts, and rules or heuristic
rules.
x    Stored facts are information or data in a designated field.
x    Rules or heuristic rules explain procedures of reasoning used to solve a
     certain problem.

Knowledge representation has been earlier discussed. It is a procedure used to
manage knowledge. A knowledge database is quite different from the
conventional database. A knowledge database does not store information like
numbers, texts, logical values and others, as found in a normal database. On the
other hand, it stores concepts and dedicated procedures that need to be done in
order to solve a problem. There are several different methods of storing
knowledge in a database. Some of the methods are predicate calculus, semantic
network, script and mainframe.
160       X TOPIC 8   EXPERT SYSTEM




(a)   Rules Creation
      Rules are divided into two operators:
      x    IF, called before (a premise or condition); and
      x    THEN, it is called effect (conclusions or actions).

      In general, rules can have a few conditions by relating each condition to the
      keywords AND, OR or a combination (AND and OR). On the contrary, it is
      better to avoid combining both in one rule.

      The example below shows how a few conditions are related to AND.

      IF<condition 1>
      AND<condition 2>
                      x
                      x
      AND<condition n>
      THEN<action>

      The next example shows how a few conditions are related to AND and OR.

      IF<condition 1>
      AND<condition 2>
      OR<condition 3>
      THEN <action>

      According to Durkin, rules can represent a relationship, suggestion,
      instruction, strategy and heuristic.

      Relationship
      IFÂtankÊ is empty
      THEN car cannot start

Suggestions
IF monsoon season
AND cloudy sky
AND weather station predicted rain
THEN you are advised to bring an umbrella

Instructions
IF car cannot start
AND ÂtankÊ is empty
THEN put petrol in the tank
TOPIC 8    EXPERT SYSTEM    W    161



Strategy
IF car cannot start
AND ÂtankÊ is empty
THEN put petrol in the tank
Step 1 is done

IF Step 1 is done
AND tank is full
THEN check the car battery
Step 2 is done

Heuristic
IF fluid spills
AND pH of the spill < 6
AND smells acidic or sour
THEN the spills is an acetic acid


8.3.2      Knowledge Acquisition

 Definition

 Knowledge acquisition is a process of gathering and transfering Âproblem-
 solving expertiseÊ from all sources of knowledge in a computer programme.


The expert information that has been acquired will be used to develop and
expand the base knowledge. The source of knowledge stated here includes
experts, journals, the Internet, online databases or research reports and
experiments.


8.3.3      Inference Engine
The inference engine is the most important component and is considered the
ÂbrainÊ of an ES. The inference engine is the knowledge process that is modelled
on the methods of human expert reasoning. It is a process in the Expert System
that pairs the facts stored in the working memory with the knowledge domain
that is stored in the knowledge database, to get the method from the problem. It
is also known as the control structure or the rule interpreter for an ES base rule.
162     X TOPIC 8     EXPERT SYSTEM




  Definition
  Inference engine is a computer programme that drives to the conclusion or
  solution and at the same time provides the reasoning methodology for
  information stored in the knowledge database.


Inference engine also provides a guideline on using the knowledge in ES by
developing an agenda that manages and controls the steps needed for solving a
problem during the consultation process executed by the user.

There are two strategies used by the inference engine when making decisions or
conclusions. These strategies are forward and backward chaining.


         ACTIVITY 8.2

       An interesting explanation of the use of strategic forward and
       backward chaining which includes a few related examples can be
       obtained from: http://geminga.it.nuigalway.ie/~f_smith/ES.ppt



The strategy of forward chaining can obtain a decision and produce more
information with fewer questions compared to backward chaining. Thus, it is
always used for large scale and complex ES. However, the weakness in this
approach is the long duration taken for processing. Certain ES developed
employs a combination of both the strategies of chaining, which is called the
mixed chaining.

(i)    Forward chaining strategy ă the inference engine starts reasoning from the
       facts provided and moves on until it achieves its decision or conclusion.
       This strategy is guided by the provided facts in the memory space and the
       premises which it can obtain them from. The inference engine will try to
       match the required premise (IF) for all rules in the knowledge database
       with the facts given, which are in its memory. If there are several rules that
       match, the solving procedures will be used. The inference engine will
       repeatedly match the rules of the basic knowledge to the data stored in its
       memory.

(ii)   Backward chaining strategy ă this strategy is the opposite of the forward
       chaining strategy. It starts from the decision and moves ÂbackwardÊ to
       obtain supporting facts for the decision made. If there are no matching facts
TOPIC 8    EXPERT SYSTEM    W    163



          that support the chosen decision, the decision will be rejected and another
          decision will be selected. The process continues until a suitable decision
          and the facts that support it are obtained.


             SELF-CHECK 8.5

          Is the inference engine reasoning process the same as your reasoning
          process? Which will you use to solve a problem? Can both processes
          be used?


8.3.4            Explanation Facility
This component acts to help the user understand how an ES reaches a certain
decision or conclusion of the problem that needs to be solved. The user can
obtain the logic or rationale for a certain decision that it makes. This component
is capable of answering questions like:

      -    Why is this question being addressed by the system?
      -    How is a decision made?
      -    On what basis is the decision made?
      -    Why are certain alternatives rejected from being a decision or solution?

Example

ES           :    Is the car going to start?
User         :    Why?
ES           :    If I know my car will not start, I may assume that the problem is due
                  to the failure of the electronic system of the car.

An expert will act based on what he or she can conclude from the answers
whereas ES responds to the question of WHY by displaying the rules it is
executing.

(a)       Explanation of WHY
          Apart from providing the final decision, an ES can explain how it comes to
          a decision.

          Developing a conventional system is done based on the defined problems
          but it is not the same for an Expert System. Thus, ES needs a justification
          facility to explain to the user all the decisions it makes.
164    X TOPIC 8        EXPERT SYSTEM



      As an example:

       ES           :    The battery of your car has failed.

       User of ES   :    HOW?

       ES           :    It is because your car cannot be started, thus, the system assumes
                         that the electronic system in your car has failed. When the
                         system finds that the voltage level is below 10V thus it is proven
                         that your car battery has failed.


      The ES responds by stepping back to the rules that the system uses to
      achieve the decision. Stepping back to the rules is how the Expert System
      does the reasoning.


8.3.5        The User Interface

            SELF-CHECK 8.6

      In your opinion, what are the differences between a user interface in
      an Expert system and in other information systems like MIS?


The user communicates with the Expert System through the user interface. It
enables the user to query the system, input information and receive advice. The
Expert System aims to provide communication between the system and the user,
as if the user were interacting with the expert. However, the Expert System is still
unable to understand normal language and general knowledge.

Occasionally, ES process language which enables interaction and communication
between the user and ES in a user-friendly manner. When ES was first
introduced, the ES interface was only text based. However, a language that was
more similar to the human language made communication more natural. Now,
certain ES provide Graphical User Interface like menus and graphics in the
Windows environment.


8.3.6        Working Memory
Another important component in an ES is the working memory. It contains facts
of problems that are happening during the consultation process with the Expert
System. The system will match the information found with the knowledge stored
TOPIC 8       EXPERT SYSTEM   W   165



in the knowledge database to consider the new facts. The conclusion obtained
will be stored in the working memory. Thus, the working memory contains the
information that is supplied by the user, or the reasoning done by the Expert
System itself.


          SELF-CHECK 8.7
      Compare and contrast the strategic forward chaining and strategic
      backward chaining.



 8.4        THE EXPERT SYSTEM CHARACTERISTICS
An Es is usually designed to have these characteristics:

(a)   The Highest Level of Expertise
      This characteristic is most useful. This expertise in an ES is comes from the
      knowledge and problem solving steps provided by the best experts in their
      own domains. This will lead towards efficiency, accuracy and imaginative
      problem solving.

(b)   Right on Time Reaction
      An Expert System must function and interact in a very reasonable period of
      time with the user. The total time must be less than the time taken by an
      expert to solve the same problem.

(c)   Accepting Incorrect Reasoning
      This type of application is used when the information used for the solution
      is unclear, vague or cannot be obtained and not in a domain that is very
      clear.

(d)   Good Reliability
      The expert system must be reliable and it must be improbable for the
      system to make a mistake.

(e)   Easily Understood
      The Expert System must be able to explain the reasoning steps during the
      execution or the inference process for the user to better understand what is
      happening. An ES must be able to explain why such actions are taken the
      same way an expert would explain the decision he made.
166       X TOPIC 8   EXPERT SYSTEM



(f)   Flexible
      Due to the large amount knowledge possessed by an ES, it is important for
      the ES to have an efficient mechanism to administer the compilation of the
      existing knowledge in it.

(g)   Symbolic Reasoning
      The Expert system represents knowledge in symbolic terms by using one
      set of symbols that represents all the concepts of the problem in the specific
      domain. All the symbols, when combined or paired, will demonstrate a
      relationship between the problems. When this relationship is represented in
      a programme they are called structured symbols.

      For example

      Statement : Ahmad has a fever
      Rule       : IF a person has a fever, THEN take Panadol
      Conclusion : Ahmad takes Panadol

(h)   Heuristic Reasoning
      An expert does efficient problem solving by relating to experience as the
      basis of reasoning. If the problem encountered is new, then the expert
      combines the knowledge and experience to solve the problem.

(i)   An example of heuristic reasoning used by an expert:
      x    I will usually check the electronic system first.
      x     Humans will not usually be infected with flu during summer.
      x    If I suspect cancer in a patient, I will check the patientÊs family
           background first.

(j)   Making Mistakes
      Since most of the knowledge in the ES database was input by humans it is
      subject to human error. This might happen due to the rules, facts, or steps
      not being considered or being wrongly input during the process of
      acquiring of knowledge.

(k)   Expanding with Tolerable Difficulties
      The problems that an ES needs to solve must be complex and difficult but
      at a tolerable level. However, the problem must not be too easy.
TOPIC 8      EXPERT SYSTEM       W     167



(l)     Focus Expertise
        Most experts are skilful and knowledgeable in their own field only. The ES
        must be made to focus on a specific domain and not mix up the knowledge
        of two experts from different domains.

      Table 8.3: The Differences between the Conventional System and the Expert System

              Conventional System                             Expert System

                                                Knowledge database and the processing
 Knowledge and processing are combined
                                                mechanism (inference) are two different
 in one programme.
                                                components.

 Programme does not make errors (only           The ES programme may be make a
 programming error).                            mistake.

 Usually it will not explain why the data
 needs to be input or how the decision is       Explanation is part of an ES component.
 achieved.

 System is operational only when fully          An ES can operate with small amount of
 developed.                                     rules.

 Step by step execution according to fixed      Execution      done       logically      and
 algorithms is necessary.                       heuristically.

                                                Can operate with sufficient or insufficient
 Needs complete and full information.
                                                information.

 Manipulates      a   large   and   effective
                                                Manipulates a big and effective database.
 database.

 Referencing and use of data.                   Referencing and use of Knowledge.

 Main objective is efficiency.                  Main objective is effectiveness.

 Easily operated with quantitative data.        Easily operated with qualitative data.


            SELF-CHECK 8.8
        List three (3) main characteristics of an Expert system and define them.
168         X TOPIC 8   EXPERT SYSTEM




    8.5        EXPERT SYSTEM DEVELOPMENT
An Expert system team must consist of:
x     A domain expert
x     Knowledge engineer
x     User

(a)     Domain Expert

    Definition
    A domain expert is a person who has the knowledge, experience, skills, steps
    special consultation skills. in a certain field or a particular subject. He should
    also be able to guide and possess unique problem solving methods and is
    b tt th th         t f       l i th fi ld

        Even though an Expert system usually models the expertise of either one or
        more experts, an ES also models expertise based on other alternative
        sources such as printed material (books, manuals, journals and others). The
        prerequisites to be a domain expert are:
        x    Knowledgeable in a particular field
        x    Has skills in solving problems.
        x    Is competent in presenting knowledge
        x    Has time management skills
        x    Must be cooperative

(b)     Knowledge Engineer
        A knowledge engineer is a person who is responsible for creating,
        developing and testing the Expert system. The prerequisites to become a
        knowledge engineer are:
        x    Must have engineering knowledge (the art and science to develop an
             Expert System)
        x    Has good communication skills
        x    Able to match problems with software
        x    Have technical knowledge (programming) in developing an expert
             system
TOPIC 8   EXPERT SYSTEM   W   169



(c)    User
       The user is one who uses the Expert System when it has been fully
       developed. He or she will help during the knowledge acquiring process by
       explaining their problems to the knowledge engineer.


8.5.1        The Software and Tools in Expert System
             Development

          SELF-CHECK 8.9

        In your opinion, can the methodology used in developing a
        conventional system be applied in developing an expert system?


An expert system developer can choose three different approaches in developing
an ES, which are:
x     Using programming language
x     Using an Expert System shell
x     Using the tools in an artificial environment
(a)    The Programming Language
       An ES can be developed using a symbolic language such as LISP or
       PROLOG, or a conventional higher-level language such as FORTRAN, C
       and PASCAL.

       LISP
       All ES developed in the early days used LISP, or tools written using the
       LISP language.

       PROLOG
       The on-going research of artificial intelligent has given birth to the
       programming language PROLOG. PROLOG is the acronym for
       'Programming in Logic'. A programme using PROLOG can be assumed to
       be a knowledge database that stores facts and rules.


           SELF-CHECK 8.10

       Compare and contrast PROLOG and LISP software.
170       X TOPIC 8     EXPERT SYSTEM




(b)     Expert System Shell
        An Expert System shell is a programme used to develop an Expert system.
        The Expert System Shell executes three (3) main functions:
        (i)     Helps the programmer build a knowledge database by permitting the
                developer to input knowledge in the knowledge representation
                structure.
        (ii)    Provides the procedures for inference or reasoning deductions based
                on the information stored in the information database and new facts
                input by the user.
        (iii) Provides the interface to let the user prepare reasoning tasks and
              questions to be queried to the system on strategic reasoning.


8.5.2           The Tools and Environment of Artificial
                Intelligence
Compared to the programming language and shell, this tool is extremely
expensive and powerful. The advantage of using this tool is that it provides a
variety in knowledge representation techniques such as rules and frames.


              ACTIVITY 8.3

      For    additional   reading,     you   are encouraged to  visit:
      http://www.denniskennedy.com/kmai01.htm to see how an artificial
      environment is created for a law firm.



 8.6            THE ADVANTAGES AND DISADVANTAGES
                OF AN EXPERT SYSTEM
There are advantages and disadvantages of an Expert system. They are listed
next.
TOPIC 8    EXPERT SYSTEM    W    171



8.6.1      The Expert System Advantages
ES usage provides many advantages. Some of the advantages are:

(a)   Consistency
      One of the advantages of an ES is that the results given are consistent. This
      might be due to the fact that there are no elements such as exhaustion and
      emotions as experienced by humans.
(b)   Hazardous Working Environment
      Through an ES, we can avoid exposing ourselves to a toxic or radioactive
      environment. An ES can take over the place of an expert to handle
      problems in a high-risk area such as a nuclear power plant.

(c)   Ability to Solve Complex and Difficult Problems
      A very difficult problem encountered by an organisation, if not taken
      seriously, can cause an adverse impact such as losses or cancellation of a
      business deal. Sometimes, the problems need to be attended to quickly. The
      problems can become more complicated when individuals or experts
      involved in solving them are absent or cannot be contacted. Thus, an ES
      serves as an alternative to experts.

(d)   Combination of Knowledge and Expertise from Various Sources
      As discussed earlier, one of the important components in an ES is the
      knowledge base. This component contains the accumulated knowledge and
      acquired or transferred expertise from many experts. Thus, an ES is
      sometimes more superior than an expert because its knowledge and
      expertise have come from many sources.

(e)   Training Tool for Trainees
      An ES can be used by trainees to learn about the knowledge-based system.
      Trainee who uses an ES would be able to observe how an expert solves a
      problem.


8.6.2      Disadvantages and Weaknesses of Expert
           System

         SELF-CHECK 8.11
      The Expert system also has weaknesses and flaws. In your opinion, do
      these weaknesses influence the quality of an Expert system?
172    X TOPIC 8     EXPERT SYSTEM



Listed below are several weaknesses concerning the use of ES.

(a)   Not Widely Used
      ES is not widely used in business firms or organisations. Due to limited
      usage, firms are still in doubt about the capability and, most definitely, the
      high cost involved in investing in an ES..

(b)   Difficult to Use
      Using an ES is very difficult and learning and mastering it requires a long
      time. This discourages managers from using ES. In one aspect, developing
      an ES that is user-friendly is the biggest challenge for ES developer..

(c)   Limited Scope
      This is the most obvious weakness in an ES; its scope is very limited to its
      field only. In the development aspect, the ES built is best developed
      because of its high accuracy. However, usage-wise decision makers face
      constantly changing problems which involve different fields that are inter-
      related.

(d)   Probable Decision Error
      The main source of the knowledge is experts. Humans make mistakes. If
      the experts input wrong information into the Expert system, this will have a
      negative impact on the results produced.

(e)   Difficult to Maintain
      The information in ES must be constantly updated to solve new problems.
      Every new problem that occurs needs new knowledge and expertise. This
      means that there must be an on-going relationship between the domain
      experts and the ES developer. This situation requires the domain experts
      update the source of knowledge and expertise to suit the current situation.

(f)   Costly Development
      The cost to consult a group of experts is not cheap, what if ES was built
      traditionally without involving the use of an Expert System shell? On the
      other hand, programming cost is high because the artificial intelligence
      technique is difficult to master and needs a very skilful programmer.

(g)   Legal and Ethical Dilemma
      We must be responsible for our actions and decisions. An expert has to take
      responsibility for the information he or she provides. . The difficult
      question here is who should shoulder the responsibility if a decision
      suggested by ES results in a negative outcome.
TOPIC 8   EXPERT SYSTEM   W   173



           SELF-CHECK 8.12
      1.    There are 10 paradigms involved in solving problems using
            an Expert system. List five paradigms.
      2.    State five main factors that distinguish humans from an
            Expert system.
      3.    Define knowledge.
      4.    State the structural differences between human problem
            solving and the Expert system.
      5.    State the types of rules below. Do the rules below represent
            relation, suggestion, instruction, strategy or heuristic?

            IF     car cannot start
            ANDÂcar voltageÊ < 10
            ANDÂhornÊ not functioning
            THUS the battery is weak

            IF     the battery is weak
            THENthe solution is to install a new battery

      (Please use your own piece of paper)




x   Expert System (ES) is a system that mimics the human capability to think and
    reason for decision-making.

x   An ES combines the use of knowledge, facts and reasoning techniques for
    decision-making.

x   An Expert system is built for two main reasons - to replace an expert or to
    help an expert.

x   The Expert system is used in various applications in multiple fields and
    sectors like medicine, engineering, education, manufacturing, marketing, tax
    planning, and many more.

x   Knowledge is understanding a subject or domain through theory or practice.
174    X TOPIC 8    EXPERT SYSTEM




x   Knowledge is also the combination and mix of information that is already
    known, and knowledge is power. From the expertÊs knowledge, the rules are
    formed.

x   Rules as knowledge representation consists of two parts - the IF part, called
    before (condition or premise) and the THEN part, called effect (conclusion or
    action).

x   The architecture of an ES is from the knowledge base, inference engine,
    explanation facility and knowledge acquisition facility.

x   The existence of ES provides positive and negative effects that need to be
    considered in the development of an Expert System.

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Topic 8 expert system

  • 1. T o p ic X Expert System 8 LEARNING OUTCOMES By the end of this topic, you should be able to: 1. Describe what an Expert System is and its applications; 2. Describe the steps involved in producing rules and information gathering; 3. List the 11 main characteristics of an Expert System; and 4. Differentiate between conventional information systems and the Expert System. X INTRODUCTION In this topic, you will learn about one of the branches of artificial intelligence, which is the Expert System. The Expert System is also known as the knowledge- based System. The Expert System comprises many types of Systems based on rules, frames and fuzzy sets. In this topic, you will also be exposed to the most popular expert system, the System based on rules. Definition Expert System is an information system that is capable of mimicking human thinking and making considerations during the process of decision-making. It is an information system that has been used to solve a problem that usually requires an expert to solve.
  • 2. TOPIC 8 EXPERT SYSTEM W 153 8.1 WHAT IS AN EXPERT SYSTEM? SELF-CHECK 8.1 Currently, the Expert System is a popular topic in the Management Information System. In your own words, explain what is an Expert System. According to Efraim Turban (2001), the Expert System comes from the Knowledge-Based Expert System terminology. Expert System (ES) is a System that uses human knowledge stored inside a computer to solve problems that requires human expertise to solve. A good ES is a system that can copy the process of reasoning in a human. What is meant by an expert? An expert is a person that has the expertise and knowledge of his specialised field. Examples of experts are a heart specialist and a mathematics expert. Through experience, an expert expands his skills to enable him to solve problems heuristically, efficiently and effectively. 8.1.1 Expert System Definition Prof. Edward Feigenbaum (1983, p.?) from Stanford University, a famous researcher on ES defines ES as: "«an intelligent computer programme that uses knowledge and reasoning procedures to solve difficult problems that need certain expertise to solve the problems." ES is developed to model the ability of an expertise in solving problems. In the process of modelling the method which an expert uses to solve a problem, ES must be able to provide users with the services and facilities that an expert can usually provide. 8.1.2 Why is an Expert System Needed? You must be thinking of the rationale behind the process of transferring the knowledge of an expert to a computer. Table 8.1 will answer your query by comparing the Expert System to that of humans.
  • 3. 154 X TOPIC 8 EXPERT SYSTEM Table 8.1: Comparisons between an Expert System and that of a Human Expert Factor Human Expert Expert System Time (can be obtained) Working days only Anytime Geography Local Anywhere Safety Cannot be replaced Can be replaced Damages Yes No Speed and Efficiency Changes Consistent Cost High Intermediate An Expert System is built because of two factors: either to replace or to help an expert. Some of the reasons for the need of an Expert System to replace an expert are: x To enable the use of expertise after working hours or at different locations. x To automate a routine task that reqquires human expertise all the time unattended, thus reducing operational costs. x To replace a retiring or an leaving employee who is an expert. x To hire an expert is costly. ACTIVITY 8.1 Has your car ever broken down? Think about how an Expert system can help a car owner. Discuss this with your course mates. The Expert System is used to: x Help experts in their routine to improve productivity. x Help experts in some of their more complex and difficult tasks so that the problem can be managed effectively. x Help an expert to obtain information needed by other experts who have forgotten about it or who are too busy to search for it.
  • 4. TOPIC 8 EXPERT SYSTEM W 155 8.1.3 Expert System Application Expert System is widely used in all types of fields and sectors like medicine, engineering, education, marketing, tax planning and more. We will study several other applications in the financial, production and military sectors. x Banking and Financial sector ă Application of EIS System used: - An Expert System that helps bank managers in making decisions on granting loans. - An Expert System that advises bank managers in giving housing loans. - An Expert System that advises insurance companies on the risks involved in insuring a customer or a company. - An Expert System that helps banks decide on whether a customer is entitled for a credit card or not. - An Expert System that identifies computer fraud and controls it. x Production industries and Military ă Application of EIS Type of Expert System used: - An Expert System capable of diagnosing some technical malfunctions in airplanes, gas turbines and helicopters. - An Expert System that helps identify threats that may put security at risk. - An Expert System that helps form and produce small mechanical items.
  • 5. 156 X TOPIC 8 EXPERT SYSTEM SELF-CHECK 8.2 Differentiate between human expertise and the Expert system: Factor Human Expertise Expert System Time (which can be obtained) Geography Security Malfunctions Performance and speed Cost Table 8.2: Problem-Solving Paradigm Problem-Solving Paradigm Example of Expert System application Control Controlling the Behaviour of the system according to specification. Design Aligning objects following limits. Diagnosis Providing reasons for system malfunction based on observation. Instruction Diagnosing and improving behaviour of students. Translation Providing reasons for situations based on data given. Assessment Comparing observation data with expectations. Planning Designing a plan of action. Prediction Providing reasons on the cause and effect of a certain decision based on situation. Selection Identifying the best selection from all alternatives and probabilities. Prescription Suggesting solution to improve a malfunction system.
  • 6. TOPIC 8 EXPERT SYSTEM W 157 Table 8.2 lists ten (10) paradigms in problem-solving that an Expert System is capable of solving. 8.2 KNOWLEDGE SELF-CHECK 8.3 Knowledge helps humans solve problems. How is knowledge used in a system? Around the 1970s, computer scientists accepted the fact that in order to enable a machine to solve intellectual problems, a machine must know how to first solve it. In other words, it had to have the 'how-to' knowledge to solve problems in a specific domain. x What is knowledge? Definition Knowledge is a theoretical or practical understanding of a subject or domain. Knowledge is a combination and mix of information that is already known, and knowledge is power. Anyone who has a certain amount of knowledge may be considered an expert. Experts are people who have power in the organisation. In any successful company, there are a certain number of first class experts and the companies will not succeed without them. As an example, Sun Microsystem has James Gosling, the founder of Java programming. x Who is fit to be called an expert? Anyone can be called an expert as long as that person has a vast knowledge of the particular field and has practical experience in a certain domain. However, the person is restricted to his or her own domain. For example, being an IT expert does not mean that the person is an expert in all IT domains but she may be an expert in intelligence systems or an expert in only the development of an intelligence agent.
  • 7. 158 X TOPIC 8 EXPERT SYSTEM x How does an expert think? The human mental process is too complex and complicated to be drafted as an algorithm. Many experts can only create rules in solving certain problems. We will learn more about the steps in referencing the knowledge acquired from an expert with the rules when we learn about the basic architecture of an Expert System. On the other hand, Figure 8.1 and 8.2 below show the different ÂthinkingÊ of an expert and a machine. Knowledge Domain Long- term Memory Advisor: Conclusion based on Short-term Memory Cases/Facts Conclusion Result Facts/Cases Reasoning Figure 8.1: Human problem-solving architectural structure Knowledge Database Domain Knowledge User: Conclusion based on Working Memory Cases/Facts Conclusion Reasoning Facts/Cases Figure 8.2: An expert system problem-solving architectural structure SELF-CHECK 8.4 Write down the differences between the human problem-solving architecture and those of the Expert System.
  • 8. TOPIC 8 EXPERT SYSTEM W 159 8.3 EXPERT SYSTEM ARCHITECTURE Figure 8.3: Basic components of an Expert System An ES merges knowledge, facts and reasoning techniques in producing a decision. In order to produce a decision, an ES fundamental architecture is required, as shown in Figure 8.3. The components are: x Knowledge base x Inference engine x Explanation facility x Knowledge acquisition facility 8.3.1 Knowledge Base A knowledge database stores two important things: facts, and rules or heuristic rules. x Stored facts are information or data in a designated field. x Rules or heuristic rules explain procedures of reasoning used to solve a certain problem. Knowledge representation has been earlier discussed. It is a procedure used to manage knowledge. A knowledge database is quite different from the conventional database. A knowledge database does not store information like numbers, texts, logical values and others, as found in a normal database. On the other hand, it stores concepts and dedicated procedures that need to be done in order to solve a problem. There are several different methods of storing knowledge in a database. Some of the methods are predicate calculus, semantic network, script and mainframe.
  • 9. 160 X TOPIC 8 EXPERT SYSTEM (a) Rules Creation Rules are divided into two operators: x IF, called before (a premise or condition); and x THEN, it is called effect (conclusions or actions). In general, rules can have a few conditions by relating each condition to the keywords AND, OR or a combination (AND and OR). On the contrary, it is better to avoid combining both in one rule. The example below shows how a few conditions are related to AND. IF<condition 1> AND<condition 2> x x AND<condition n> THEN<action> The next example shows how a few conditions are related to AND and OR. IF<condition 1> AND<condition 2> OR<condition 3> THEN <action> According to Durkin, rules can represent a relationship, suggestion, instruction, strategy and heuristic. Relationship IFÂtankÊ is empty THEN car cannot start Suggestions IF monsoon season AND cloudy sky AND weather station predicted rain THEN you are advised to bring an umbrella Instructions IF car cannot start AND ÂtankÊ is empty THEN put petrol in the tank
  • 10. TOPIC 8 EXPERT SYSTEM W 161 Strategy IF car cannot start AND ÂtankÊ is empty THEN put petrol in the tank Step 1 is done IF Step 1 is done AND tank is full THEN check the car battery Step 2 is done Heuristic IF fluid spills AND pH of the spill < 6 AND smells acidic or sour THEN the spills is an acetic acid 8.3.2 Knowledge Acquisition Definition Knowledge acquisition is a process of gathering and transfering Âproblem- solving expertiseÊ from all sources of knowledge in a computer programme. The expert information that has been acquired will be used to develop and expand the base knowledge. The source of knowledge stated here includes experts, journals, the Internet, online databases or research reports and experiments. 8.3.3 Inference Engine The inference engine is the most important component and is considered the ÂbrainÊ of an ES. The inference engine is the knowledge process that is modelled on the methods of human expert reasoning. It is a process in the Expert System that pairs the facts stored in the working memory with the knowledge domain that is stored in the knowledge database, to get the method from the problem. It is also known as the control structure or the rule interpreter for an ES base rule.
  • 11. 162 X TOPIC 8 EXPERT SYSTEM Definition Inference engine is a computer programme that drives to the conclusion or solution and at the same time provides the reasoning methodology for information stored in the knowledge database. Inference engine also provides a guideline on using the knowledge in ES by developing an agenda that manages and controls the steps needed for solving a problem during the consultation process executed by the user. There are two strategies used by the inference engine when making decisions or conclusions. These strategies are forward and backward chaining. ACTIVITY 8.2 An interesting explanation of the use of strategic forward and backward chaining which includes a few related examples can be obtained from: http://geminga.it.nuigalway.ie/~f_smith/ES.ppt The strategy of forward chaining can obtain a decision and produce more information with fewer questions compared to backward chaining. Thus, it is always used for large scale and complex ES. However, the weakness in this approach is the long duration taken for processing. Certain ES developed employs a combination of both the strategies of chaining, which is called the mixed chaining. (i) Forward chaining strategy ă the inference engine starts reasoning from the facts provided and moves on until it achieves its decision or conclusion. This strategy is guided by the provided facts in the memory space and the premises which it can obtain them from. The inference engine will try to match the required premise (IF) for all rules in the knowledge database with the facts given, which are in its memory. If there are several rules that match, the solving procedures will be used. The inference engine will repeatedly match the rules of the basic knowledge to the data stored in its memory. (ii) Backward chaining strategy ă this strategy is the opposite of the forward chaining strategy. It starts from the decision and moves ÂbackwardÊ to obtain supporting facts for the decision made. If there are no matching facts
  • 12. TOPIC 8 EXPERT SYSTEM W 163 that support the chosen decision, the decision will be rejected and another decision will be selected. The process continues until a suitable decision and the facts that support it are obtained. SELF-CHECK 8.5 Is the inference engine reasoning process the same as your reasoning process? Which will you use to solve a problem? Can both processes be used? 8.3.4 Explanation Facility This component acts to help the user understand how an ES reaches a certain decision or conclusion of the problem that needs to be solved. The user can obtain the logic or rationale for a certain decision that it makes. This component is capable of answering questions like: - Why is this question being addressed by the system? - How is a decision made? - On what basis is the decision made? - Why are certain alternatives rejected from being a decision or solution? Example ES : Is the car going to start? User : Why? ES : If I know my car will not start, I may assume that the problem is due to the failure of the electronic system of the car. An expert will act based on what he or she can conclude from the answers whereas ES responds to the question of WHY by displaying the rules it is executing. (a) Explanation of WHY Apart from providing the final decision, an ES can explain how it comes to a decision. Developing a conventional system is done based on the defined problems but it is not the same for an Expert System. Thus, ES needs a justification facility to explain to the user all the decisions it makes.
  • 13. 164 X TOPIC 8 EXPERT SYSTEM As an example: ES : The battery of your car has failed. User of ES : HOW? ES : It is because your car cannot be started, thus, the system assumes that the electronic system in your car has failed. When the system finds that the voltage level is below 10V thus it is proven that your car battery has failed. The ES responds by stepping back to the rules that the system uses to achieve the decision. Stepping back to the rules is how the Expert System does the reasoning. 8.3.5 The User Interface SELF-CHECK 8.6 In your opinion, what are the differences between a user interface in an Expert system and in other information systems like MIS? The user communicates with the Expert System through the user interface. It enables the user to query the system, input information and receive advice. The Expert System aims to provide communication between the system and the user, as if the user were interacting with the expert. However, the Expert System is still unable to understand normal language and general knowledge. Occasionally, ES process language which enables interaction and communication between the user and ES in a user-friendly manner. When ES was first introduced, the ES interface was only text based. However, a language that was more similar to the human language made communication more natural. Now, certain ES provide Graphical User Interface like menus and graphics in the Windows environment. 8.3.6 Working Memory Another important component in an ES is the working memory. It contains facts of problems that are happening during the consultation process with the Expert System. The system will match the information found with the knowledge stored
  • 14. TOPIC 8 EXPERT SYSTEM W 165 in the knowledge database to consider the new facts. The conclusion obtained will be stored in the working memory. Thus, the working memory contains the information that is supplied by the user, or the reasoning done by the Expert System itself. SELF-CHECK 8.7 Compare and contrast the strategic forward chaining and strategic backward chaining. 8.4 THE EXPERT SYSTEM CHARACTERISTICS An Es is usually designed to have these characteristics: (a) The Highest Level of Expertise This characteristic is most useful. This expertise in an ES is comes from the knowledge and problem solving steps provided by the best experts in their own domains. This will lead towards efficiency, accuracy and imaginative problem solving. (b) Right on Time Reaction An Expert System must function and interact in a very reasonable period of time with the user. The total time must be less than the time taken by an expert to solve the same problem. (c) Accepting Incorrect Reasoning This type of application is used when the information used for the solution is unclear, vague or cannot be obtained and not in a domain that is very clear. (d) Good Reliability The expert system must be reliable and it must be improbable for the system to make a mistake. (e) Easily Understood The Expert System must be able to explain the reasoning steps during the execution or the inference process for the user to better understand what is happening. An ES must be able to explain why such actions are taken the same way an expert would explain the decision he made.
  • 15. 166 X TOPIC 8 EXPERT SYSTEM (f) Flexible Due to the large amount knowledge possessed by an ES, it is important for the ES to have an efficient mechanism to administer the compilation of the existing knowledge in it. (g) Symbolic Reasoning The Expert system represents knowledge in symbolic terms by using one set of symbols that represents all the concepts of the problem in the specific domain. All the symbols, when combined or paired, will demonstrate a relationship between the problems. When this relationship is represented in a programme they are called structured symbols. For example Statement : Ahmad has a fever Rule : IF a person has a fever, THEN take Panadol Conclusion : Ahmad takes Panadol (h) Heuristic Reasoning An expert does efficient problem solving by relating to experience as the basis of reasoning. If the problem encountered is new, then the expert combines the knowledge and experience to solve the problem. (i) An example of heuristic reasoning used by an expert: x I will usually check the electronic system first. x Humans will not usually be infected with flu during summer. x If I suspect cancer in a patient, I will check the patientÊs family background first. (j) Making Mistakes Since most of the knowledge in the ES database was input by humans it is subject to human error. This might happen due to the rules, facts, or steps not being considered or being wrongly input during the process of acquiring of knowledge. (k) Expanding with Tolerable Difficulties The problems that an ES needs to solve must be complex and difficult but at a tolerable level. However, the problem must not be too easy.
  • 16. TOPIC 8 EXPERT SYSTEM W 167 (l) Focus Expertise Most experts are skilful and knowledgeable in their own field only. The ES must be made to focus on a specific domain and not mix up the knowledge of two experts from different domains. Table 8.3: The Differences between the Conventional System and the Expert System Conventional System Expert System Knowledge database and the processing Knowledge and processing are combined mechanism (inference) are two different in one programme. components. Programme does not make errors (only The ES programme may be make a programming error). mistake. Usually it will not explain why the data needs to be input or how the decision is Explanation is part of an ES component. achieved. System is operational only when fully An ES can operate with small amount of developed. rules. Step by step execution according to fixed Execution done logically and algorithms is necessary. heuristically. Can operate with sufficient or insufficient Needs complete and full information. information. Manipulates a large and effective Manipulates a big and effective database. database. Referencing and use of data. Referencing and use of Knowledge. Main objective is efficiency. Main objective is effectiveness. Easily operated with quantitative data. Easily operated with qualitative data. SELF-CHECK 8.8 List three (3) main characteristics of an Expert system and define them.
  • 17. 168 X TOPIC 8 EXPERT SYSTEM 8.5 EXPERT SYSTEM DEVELOPMENT An Expert system team must consist of: x A domain expert x Knowledge engineer x User (a) Domain Expert Definition A domain expert is a person who has the knowledge, experience, skills, steps special consultation skills. in a certain field or a particular subject. He should also be able to guide and possess unique problem solving methods and is b tt th th t f l i th fi ld Even though an Expert system usually models the expertise of either one or more experts, an ES also models expertise based on other alternative sources such as printed material (books, manuals, journals and others). The prerequisites to be a domain expert are: x Knowledgeable in a particular field x Has skills in solving problems. x Is competent in presenting knowledge x Has time management skills x Must be cooperative (b) Knowledge Engineer A knowledge engineer is a person who is responsible for creating, developing and testing the Expert system. The prerequisites to become a knowledge engineer are: x Must have engineering knowledge (the art and science to develop an Expert System) x Has good communication skills x Able to match problems with software x Have technical knowledge (programming) in developing an expert system
  • 18. TOPIC 8 EXPERT SYSTEM W 169 (c) User The user is one who uses the Expert System when it has been fully developed. He or she will help during the knowledge acquiring process by explaining their problems to the knowledge engineer. 8.5.1 The Software and Tools in Expert System Development SELF-CHECK 8.9 In your opinion, can the methodology used in developing a conventional system be applied in developing an expert system? An expert system developer can choose three different approaches in developing an ES, which are: x Using programming language x Using an Expert System shell x Using the tools in an artificial environment (a) The Programming Language An ES can be developed using a symbolic language such as LISP or PROLOG, or a conventional higher-level language such as FORTRAN, C and PASCAL. LISP All ES developed in the early days used LISP, or tools written using the LISP language. PROLOG The on-going research of artificial intelligent has given birth to the programming language PROLOG. PROLOG is the acronym for 'Programming in Logic'. A programme using PROLOG can be assumed to be a knowledge database that stores facts and rules. SELF-CHECK 8.10 Compare and contrast PROLOG and LISP software.
  • 19. 170 X TOPIC 8 EXPERT SYSTEM (b) Expert System Shell An Expert System shell is a programme used to develop an Expert system. The Expert System Shell executes three (3) main functions: (i) Helps the programmer build a knowledge database by permitting the developer to input knowledge in the knowledge representation structure. (ii) Provides the procedures for inference or reasoning deductions based on the information stored in the information database and new facts input by the user. (iii) Provides the interface to let the user prepare reasoning tasks and questions to be queried to the system on strategic reasoning. 8.5.2 The Tools and Environment of Artificial Intelligence Compared to the programming language and shell, this tool is extremely expensive and powerful. The advantage of using this tool is that it provides a variety in knowledge representation techniques such as rules and frames. ACTIVITY 8.3 For additional reading, you are encouraged to visit: http://www.denniskennedy.com/kmai01.htm to see how an artificial environment is created for a law firm. 8.6 THE ADVANTAGES AND DISADVANTAGES OF AN EXPERT SYSTEM There are advantages and disadvantages of an Expert system. They are listed next.
  • 20. TOPIC 8 EXPERT SYSTEM W 171 8.6.1 The Expert System Advantages ES usage provides many advantages. Some of the advantages are: (a) Consistency One of the advantages of an ES is that the results given are consistent. This might be due to the fact that there are no elements such as exhaustion and emotions as experienced by humans. (b) Hazardous Working Environment Through an ES, we can avoid exposing ourselves to a toxic or radioactive environment. An ES can take over the place of an expert to handle problems in a high-risk area such as a nuclear power plant. (c) Ability to Solve Complex and Difficult Problems A very difficult problem encountered by an organisation, if not taken seriously, can cause an adverse impact such as losses or cancellation of a business deal. Sometimes, the problems need to be attended to quickly. The problems can become more complicated when individuals or experts involved in solving them are absent or cannot be contacted. Thus, an ES serves as an alternative to experts. (d) Combination of Knowledge and Expertise from Various Sources As discussed earlier, one of the important components in an ES is the knowledge base. This component contains the accumulated knowledge and acquired or transferred expertise from many experts. Thus, an ES is sometimes more superior than an expert because its knowledge and expertise have come from many sources. (e) Training Tool for Trainees An ES can be used by trainees to learn about the knowledge-based system. Trainee who uses an ES would be able to observe how an expert solves a problem. 8.6.2 Disadvantages and Weaknesses of Expert System SELF-CHECK 8.11 The Expert system also has weaknesses and flaws. In your opinion, do these weaknesses influence the quality of an Expert system?
  • 21. 172 X TOPIC 8 EXPERT SYSTEM Listed below are several weaknesses concerning the use of ES. (a) Not Widely Used ES is not widely used in business firms or organisations. Due to limited usage, firms are still in doubt about the capability and, most definitely, the high cost involved in investing in an ES.. (b) Difficult to Use Using an ES is very difficult and learning and mastering it requires a long time. This discourages managers from using ES. In one aspect, developing an ES that is user-friendly is the biggest challenge for ES developer.. (c) Limited Scope This is the most obvious weakness in an ES; its scope is very limited to its field only. In the development aspect, the ES built is best developed because of its high accuracy. However, usage-wise decision makers face constantly changing problems which involve different fields that are inter- related. (d) Probable Decision Error The main source of the knowledge is experts. Humans make mistakes. If the experts input wrong information into the Expert system, this will have a negative impact on the results produced. (e) Difficult to Maintain The information in ES must be constantly updated to solve new problems. Every new problem that occurs needs new knowledge and expertise. This means that there must be an on-going relationship between the domain experts and the ES developer. This situation requires the domain experts update the source of knowledge and expertise to suit the current situation. (f) Costly Development The cost to consult a group of experts is not cheap, what if ES was built traditionally without involving the use of an Expert System shell? On the other hand, programming cost is high because the artificial intelligence technique is difficult to master and needs a very skilful programmer. (g) Legal and Ethical Dilemma We must be responsible for our actions and decisions. An expert has to take responsibility for the information he or she provides. . The difficult question here is who should shoulder the responsibility if a decision suggested by ES results in a negative outcome.
  • 22. TOPIC 8 EXPERT SYSTEM W 173 SELF-CHECK 8.12 1. There are 10 paradigms involved in solving problems using an Expert system. List five paradigms. 2. State five main factors that distinguish humans from an Expert system. 3. Define knowledge. 4. State the structural differences between human problem solving and the Expert system. 5. State the types of rules below. Do the rules below represent relation, suggestion, instruction, strategy or heuristic? IF car cannot start ANDÂcar voltageÊ < 10 ANDÂhornÊ not functioning THUS the battery is weak IF the battery is weak THENthe solution is to install a new battery (Please use your own piece of paper) x Expert System (ES) is a system that mimics the human capability to think and reason for decision-making. x An ES combines the use of knowledge, facts and reasoning techniques for decision-making. x An Expert system is built for two main reasons - to replace an expert or to help an expert. x The Expert system is used in various applications in multiple fields and sectors like medicine, engineering, education, manufacturing, marketing, tax planning, and many more. x Knowledge is understanding a subject or domain through theory or practice.
  • 23. 174 X TOPIC 8 EXPERT SYSTEM x Knowledge is also the combination and mix of information that is already known, and knowledge is power. From the expertÊs knowledge, the rules are formed. x Rules as knowledge representation consists of two parts - the IF part, called before (condition or premise) and the THEN part, called effect (conclusion or action). x The architecture of an ES is from the knowledge base, inference engine, explanation facility and knowledge acquisition facility. x The existence of ES provides positive and negative effects that need to be considered in the development of an Expert System.