What does mean Expert System? with Advantages and Disadvantages

An expert system is a computer program that is designed to emulate and mimic human intelligence, skills or behavior. An expert system is an advanced computer application that is implemented for the purpose of providing solutions to complex problems, or to clarify uncertainties through the use of non-algorithmic programs where normally human expertise will be needed. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if-then rules rather than through conventional procedural code. Expert systems are most common in the complex problem domain and are considered as widely used alternatives in searching for solutions that require the existence of specific human expertise. So, what is the question; What does mean Expert System? with Advantages and Disadvantages.

Here are explained; What is Expert System? with Advantages and Disadvantages.

Expert systems are most common in the complex problem domain and are considered as widely used alternatives in searching for solutions that require the existence of specific human expertise. The expert system is also able to justify its provided solutions based on the knowledge and data from past users. Normally expert systems are used in making business marketing strategic decisions, analyzing the performance of real-time systems, configuring computers and perform many other functions which normally would require the existence of human expertise.

The difference between an expert system with a normal problem-solving system is that the latter is a system where both programs and data structures are encoded, while for an expert system only the data structures are hard-coded and no problem-specific information is encoded in the program structure. Instead, the knowledge of a human expertise is captured and codified in a process known as knowledge engineering.

Hence, whenever a particular problem requires the assistance of a certain human expertise to provide a solution, the human expertise which has been codified will be used and processed in order to provide a rational and logical solution. This knowledge-based expert system enables the system to be frequently added with new knowledge and adapt accordingly to meet new requirements from the ever-changing and unpredictable environment.

Advantages of Using Expert System:

An expert system has been reliably used in the business world to gain tactical advantages and forecast the market’s condition. In this globalization era where every decision made in the business world is critical for success, the assistance provided from an expert system is undoubtedly essential and highly reliable for an organization to succeed.

Examples given below will be the advantages for the implementation of an expert system in business:

  • Providing consistent solutions: It can provide consistent answers for repetitive decisions, processes, and tasks. As long as the rule base in the system remains the same, regardless of how many times similar problems are being tested, the final conclusions drawn will remain the same.
  • Provides reasonable explanations: It has the ability to clarify the reasons why the conclusion was drawn and be why it is considered as the most logical choice among other alternatives. If there are any doubts in concluding a certain problem, it will prompt some questions for users to answer in order to process the logical conclusion.
  • Overcome human limitations: It does not have human limitations and can work around the clock continuously. Users will be able to frequently use it in seeking solutions. The knowledge of experts is an invaluable asset for the company. It can store the knowledge and use it as long as the organization needs.
  • Easy to adapt to new conditions: Unlike humans who often have troubles in adapting in new environments, an expert system has high adaptability and can meet new requirements in a short period of time. It also can capture new knowledge from an expert and use it as inference rules to solve new problems.

Disadvantages of Using Expert System:

Although the expert system does provide many significant advantages, it does have its drawbacks as well.

Examples given below will be the disadvantages for the implementation of an expert system in business:

  • Lacks common sense: It lacks common sense needed in some decision making since all the decisions made are based on the inference rules set in the system. It also cannot make creative and innovative responses as human experts would in unusual circumstances.
  • High implementation and maintenance cost: The implementation of an expert system in business will be a financial burden for smaller organizations since it has high development cost as well as the subsequent recurring costs to upgrade the system to adapt in the new environment.
  • Difficulty in creating inference rules: Domain experts will not be able to always explain their logic and reasoning needed for the knowledge engineering process. Hence, the task of codifying out the knowledge is highly complex and may require high
  • May provide wrong solutions: It is not error-free. There may be errors occurred in the processing due to some logic mistakes made in the knowledge base, which it will then provide the wrong solutions.

Classified of Expert System:

A good expert system is expected to grow as it learns from user feedback. Feedback is incorporated into the knowledge base as appropriate to make the expert system smarter. The dynamism of the application environment for expert systems is based on the individual dynamism of the components. This can be classified as follows:

Most dynamic: Working memory. The contents of the working memory, sometimes called the data structure, changes with each problem situation. Consequently, it is the most dynamic-component of an expert system, assuming, of course, that it is kept current.

Knowledgebase: The knowledge base need not change unless a new piece of information arises that indicates a change in the problem-solving procedure. Changes in the knowledge base should be carefully evaluated before being implemented. In effect, changes should not be based on just one consultation experience. For example, a rule that is found to be irrelevant less than one problem situation may turn out to be crucial in solving other problems.

Least dynamic: Inference engine. Because of the strict control and coding structure of an inference engine, changes are made only if absolutely necessary to correct a bug or enhance the inferential process. Commercial inference engines, in particular, change only at the discretion of the developer. Since frequent updates can be disruptive and costly to clients, most commercial software developers try to minimize the frequency of updates.

Nageshwar Das

Nageshwar Das, BBA graduation with Finance and Marketing specialization, and CEO, Web Developer, & Admin in www.ilearnlot.com.

Published by
Nageshwar Das

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