University Report: MITS5509 Intelligent Systems Expert System

This report analyzes an expert system, a key component of artificial intelligence, based on a paper by Mehmet R. Tolun and Kasim Oztoprak. The report details the expert system's architecture, comprising a knowledge base and an inference engine, and discusses forward and backward chaining. It explores the system's components, including user interfaces, knowledge acquisition facilities, and explanation facilities. The report outlines the two main phases of expert system building: knowledge elicitation and rule-based expert systems. It also covers the advantages, such as the capacity to store information and minimize costs, and limitations, such as the inability to make decisions based on common sense. The report also mentions the applications of expert systems in various fields, like medicine and education, and concludes with the importance of expert systems in the development of AI.

Running head: EXPERT SYSTEM
Name of the Assignment: Intelligent Systems for Analytics
Name of the Paper: Expert System
Names of the authors of the Paper: Mehmet R. Tolun and Kasim Oztoprak
Name of the Student:
Student ID.:
Name of the University:
Author note:

EXPERT SYSTEM
Table of Contents
Introduction:....................................................................................................................................2
Discussion:.......................................................................................................................................2
Conclusion:......................................................................................................................................6
References:......................................................................................................................................7
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Introduction:
The intelligent systems are internet connected systems of computers having the capacity
of gathering data and perform analysis over the data without a need of human assistance. It is one
of the major components of the artificial intelligence which makes use of this functionality to
operate [2]. The Expert system is one of the earliest research fields in the Artificial Intelligence
Technology. As the information technology has advanced considerably, the Expert system is
often considered to be AI.
In this report we will discuss about the paper that has been written by Mehmet R. Tolun
and Kasim Oztoprak which addresses the expert systems [3]. Firstly we will discuss about the
facts that has been covered in the paper by the author and the then we will identify different
issues regarding the technology that has been addressed in the paper. We will determine the
research methodology that has been used by the researcher to undertake the research.
Discussion:
As discussed by the author, the Expert System has two chief components and they are the
Knowledge Base and the Inference Engine. All the knowledge regarding the domain of the
expert is stored in the Knowledge Base. Starting from the simplest fact about the system to the
most complicated structure of the system is stored in this base [4]. The knowledge base also
consists of the rules and regulations regarding the expert’s skills regarding the domain which is
taken into consideration. Inference engine is phase of the technology which can be acquired with
the help of the knowledge base. There are numerous phases in the inference engine phase which
depends upon the IF - THEN rule of the Knowledge Base in the Expert System. The inference
engine is developed in the expert system after the enlargement of the knowledge base in the
technology.
The inference engine has certain notable features as well, and they are the forward
chaining and the back ward chaining. The forwards chaining is the process of moving from the
known facts of the system towards the application of the inference rules and regulation in order
to extract more data and keeps on moving towards the accomplishment of the goal or the target.
The backward chaining in the other hand is the way in which the engine starts from the goal and
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comes backwards to determine the rules for satisfying the knowledge or facts required [5]. As
one of the basic tools for the Artificial Intelligence, Expert System, along with its two parts plays
a very significant role.
The authors here, Tolun, Mehmet & Sahin, Seda & Oztoprak, Kasim, says that the expert
system follows a general architecture which is for emulating the ability of decision making of an
expert or a human [9]. This technology was developed for solving complex problems and
reasoning for which it needs an interface and other features as well. As described by them, the
Experts system has a User Interface, Knowledge Acquisition Facility and the Explanation
facility, Inference Engine Agenda, Knowledge base and Working Memory.
The User Interface is the process by which the user establish a connection with the Expert
System with the help of the communication. The Explanation facility helps in explaining the
system’s reasoning to the user who are trying to operate it. The next in line is the Knowledge
Acquisition which is an automatic facility allowing the user to enter the knowledge into the
system. The Knowledge Engineer do not have to code the knowledge in the system in this case.
The inference engines helps in generating the inferences such that the rules and regulation of the
system are followed and satisfied. This phase helps in prioritizing the rules and execution of the
rules with the highest priority [6]. There is a small part in the inference engine which is known as
the agenda, which is a list of rules which are selected by the inference engine itself. The patterns
of these rules must be satisfied in order to operate the ES satisfactorily and reach the goal. The
architecture of the Expert Systems is given in the figure below.
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Knowledge Base
Inference
Engine Working
memory (Facts)
Explanation
Facility Knowledge
Acquisition Facility
User Interface
Agenda

EXPERT SYSTEM
There are two main phase in building the Expert System and they are the Knowledge
Elicitation phase and the Rule Based Expert system phase consisting of the knowledge
representation and inferencing phase. The first phase as discussed by the author is the phase of
obtaining the knowledge and the next phase is for the representation of the obtained knowledge
such that the inferencing can help in reaching the goal. The knowledge Elicitation phase of the
Expert system gathers the knowledge by the surveys, structured and the unstructured interviews
and many other possible ways. The Rule Based ES helps in application of the rules following IF-
THEN conditions to the knowledge. The IF part of the knowledge is used as the Antecedents and
the THEN part is consequent of the knowledge [7]. With the help of the Case Study research
Methodology, the Authors have tactically explained the working of the inference engine and the
entire expert system based on that. The Advantages of the Expert system includes the capacity of
storing enormous amount of information, minimization of the cost for training the employee for
doing several task in the organization, centralization of the process of the decision making,
minimizing the time taken for solving problems and many more.
All though there are numerous benefits of the technology, there are certain limitations of
the Expert System as well, which includes the fact that the ES works better in the narrow
domain. That is it is incapable of making decisions based on the common senses. It is seen that
the human are capable of generating more creative responses than the machine which is one of
the major drawback of the AI systems. All the systems are capable of reducing the human errors,
and combines several human intelligences, it is not capable of explaining the logic behind the
decision making activity which it has performed so far [8]. However, the knowledge that are
transferred to the ES are based in the perception of the experts who are dealing with the
transferring of the knowledge, thus any sort of unintended biasness results in drawing faulty
conclusions. However, the authors have beautifully explained the bottlenecks of developing an
expert system which is very essential in the terms of the Artificial Intelligence.
The Expert systems have numerous application in the contemporary information
technology and the information system. There are numerous classification of the expert system
which are in use at the present. The commercial shells makes use of the technology for the
development of the EXSYS Corvid for the Windows Operating Systems, or the EXSYS Corvid
Core for the Apple operating system or the Mac OS ten. The same technology that is the Expert
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system, is used in providing suggestion to the students via a web based service known as the
www.MyMajors.com. There are numerous other use of the expert system that has been discussed
in brief in the article. The Expert systems have been implemented in the medical systems as well,
known as the MYCIN, for the treatment of the bacterial infections in the people. In the recent
years the Medical Expert System has shown tremendous development in the health sector which
can be considered as one of the achievement milestone for the technology.
As per the author the Expert System is considered to be one of the well-developed system
which has successfully reached its maturity stage. However, one of the major obligation in the
development of Experts system is the usage of the empirical and the heuristic knowledge for the
development of the knowledge rather than using the deep knowledge. Hence, we can say that the
development of the system based on the Experts system in the contemporary world plays a
significant role [10]. The Artificial intelligence which is one of the most important aspect of the
industry as well as the society largely depends upon this system for enhancing the growth of the
technology.
Conclusion:
From the above research paper we can say that the authors have depicted a clear image of
the Experts system, their architecture, their advantages and limitations. With the help of the case
studies and simple examples the concept of the technology has been clarified properly. The
Expert system which is considered to be one of the major part in the development of the present
day Artificial intelligence has numerous benefits which can be incorporated in the world in
numerous ways. The application of the technology includes usage in the field of medicines, or
usage in the field of the education for the purpose of the decision making, the technology is
expected to grow further in the future which will help in the process of the development of the
machine learning, improvement of the knowledge bases and many more. From this research
study, we have successfully understood the importance of the Expert System in the development
of the AI for more benefits to the organization.
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References:
[1] Abbas, A.K., Bashikh, A.A., Abbas, H. and Mohammed, H.Q., 2019. Intelligent decisions to
stop or mitigate lost circulation based on machine learning. Energy, 183, pp.1104-1113.
[2] Abu Ghali, M.J., Abu Ayyad, A., Abu-Naser, S.S. and Abu Laban, M., An intelligent
tutoring system for teaching english grammar, 2018.
[3] Abu-Nasser, B., Medical expert systems survey, International Journal of Engineering and
Information Systems (IJEAIS), 1(7), pp.218-224, 2017.
[4] Haddad, M., Sanders, D., Bausch, N., Tewkesbury, G., Gegov, A. and Hassan, M., 2018,
September. Learning to make intelligent decisions using an Expert System for the intelligent
selection of either PROMETHEE II or the Analytical Hierarchy Process. In Proceedings of
SAI Intelligent Systems Conference (pp. 1303-1316). Springer, Cham.
[5] He, C. and Li, Y., 2017, May. A survey of intelligent decision support system. In 2017 7th
International Conference on Applied Science, Engineering and Technology (ICASET 2017).
Atlantis Press.
[6]
[7] Leo Kumar, S.P., 2019. Knowledge-based expert system in manufacturing planning: state-
of-the-art review. International Journal of Production Research, 57(15-16), pp.4766-4790.
[8] Rybina, G.V. and Blokhin, Y.M., Use of intelligent planning for integrated expert systems
development, In 2016 IEEE 8th International Conference on Intelligent Systems (IS) (pp.
295-300). IEEE, 2016, September.
[9] Sanders, D., Okono, O., Langner, M., Hassan, M., Khaustov, S. and Omoarebun, P., Using a
simple expert system to assist a powered wheelchair user, In Proceedings of SAI Intelligent
Systems Conference (pp. 662-679), Springer, Cham, 2019, September.
[10] Tolun, Mehmet & Sahin, Seda & Oztoprak, Kasim, Expert Systems.
10.1002/0471238961.0524160518011305.a01.pub2, (2016).
[11] Wagner, W.P., 2017. Trends in expert system development: A longitudinal content
analysis of over thirty years of expert system case studies. Expert systems with
applications, 76, pp.85-96.
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