Expert Systems in artificial intelligence are those systems that can solve complex problems and that can act as the highest level of human expertise and intelligence. The expert systems system works as efficiently as human beings perform. It is mainly designed using artificial intelligence basic concepts, tools, and technologies, algorithms and possesses expert knowledge in a specific field.

Capabilities of an Expert System

  1. Explaining the concepts

It behaves similarly to humans. It can easily explain the things as human beings are doing.

2. Give Advice

It also provides advice on multiple things.

3. Helpful in decision making

It assists in deciding on several things.

4. Predicting results

It can also forecast ability. It gives predictions on several topics in advance.

5. Generate relevant Output

It can give accurate results of the problems for an adequate knowledge base.

Components of Expert Systems

There are the following components of the expert systems

Components of Expert system
Components of Expert system
  1. User Interface
  2. Inference Engine
  3. Knowledge base
  1. User interface

The user interface is the main part of the expert system. Working of the user interface is as under:-

  • It fetches queries in a readable form.
  • In this step, it passes the query to the inference engine.
  • At last, it shows the outcomes to the user.

2. Inference engine

It works similarly in the expert system as the human brain in the human body. It makes use of specific rules to work on. It uses the extraction of knowledge from the knowledge base. Basic tasks of the inference engine are:

  • It helps in deducting the problem to find the solution.
  • It gives reasoning about the information.

3.Knowledgebase

The knowledge base includes data, information, and past experiences collection. Two types of knowledge are factual knowledge and heuristic knowledge. The knowledge which is used by knowledge engineers and scholars is called factual knowledge. Heuristic Knowledge is based on guessing and accurate judgment.

Knowledgebase mainly focuses on:

  • Knowledge representation
  • Knowledge acquisition

Knowledge is used by IF-THEN-ELSE rules. The knowledge representation is used for organizing and formalizing knowledge in the knowledge base.

Knowledge acquisition focuses on the completeness, quality, and accuracy of the information stored in the knowledge base.

Applications of the Expert System

There is a wide number of applications in the expert system. Following are the major ones

Application AreasDescription
Medical DomainFrom nanobots to assisting robots, an expert system is everywhere.
FinanceIt is used in stock marketing, fraud detection

And airline scheduling.

AutomobilesSelf-driving cars are an example of an expert system in this area.
Process control systemsPhysical processes based on monitoring come under this category.
DesigningDesigning of the camera lens and automobile design
Knowledge domainFind out faults in vehicles.

 

Process of building an Expert System

Determine the problem characteristics

It mainly focuses on knowing the problem area and what are features that are associated with the problem.

Define the problem

In this, the main problem with which an expert system needs to do work is defined. This can be fulfilled if both the Knowledge Engineer and domain expert work incoherence.

Knowledge Engineer role

He translates the entire knowledge into a computer-readable or understandable form. He is responsible for designing an inference engine and reasoning structure. He can use this whenever he needs this.

Knowledge Expert role

Knowledge expert gives an explanation when there is an irrelevant kind of knowledge is there. He gives the appropriate reasoning at that time.

Examples of Expert System

DENDRAL: It is used for chemical analysis. It uses to predict the molecular structure of the elements.

MYCIN: It identifies disease-causing bacteria and also recommends medicine based on the patient’s parameters.

CaDet: It identifies disease cancer in early stages in the patients

DXplain: It explains about different diseases based on searching by the doctor.

PXDES: It measures the lung cancer degree based on the patient’s data.

R1/XCON: It is used to select a computer system based on user needs.

Benefits of the Expert System

Availability: They are available easily because of the daily number of software development is there.

Less error rate: Chances of errors are more in the case of human beings but it generates fewer errors.

Less cost: Production cost is low not that much high which can make them affordable.

High Speed: They work fast as compare to humans.

Responsiveness: They don’t feel tired like humans and can work without being tired.

Decision making: It helps in taking relevant decisions.

Fast solutions: In narrow areas of specialization it offers fast solutions.

Complex problems: It can solve complex problems.

Limitations of the Expert System

Maintenance: Expert systems are difficult to maintain. Its maintenance cost is very high.

Lack of trust: These systems are not more reliable these can cause failure in some cases.

Conclusion: These systems never reach towards conclusions.

High development costs: For making the expert system, the initial development cost is very high.

Conclusion

Artificial Intelligence is very vast. Daily, researchers and scientists are working to make the number of Expert systems. Every system which has advantages also has disadvantages too. In this blog, we have discussed the Expert systems, its application areas, its process, benefits, and limitations. If there is any query, feel free to ask me in the comment section

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