Advantages and Disadvantages of Expert System | Characteristics & Features

In this blog post, we are going to explain about various advantages and disadvantages of expert system as well as characteristics of expert system in artificial intelligence with ease. Make ensure that at the end of this article, you will definitely completely educated about merits and demerits of expert system without any hassle.

Expert System Definition

Expert System is a computer program that imitates the judgment and behavior of a human or an organization that has expert knowledge and experience in a particular field.

Expert System

Generally, there is a knowledge base in this type of system in which there is an accumulated experience and there is a set of rules to base the basis of knowledge in each particular situation described for the program. Sophisticated specialist systems can be enhanced with a knowledge base or addition of rules set.

Advantages of Expert System

There are many important benefits of expert system. All mention below such as:

Click Here – Expert System in Artificial Intelligence with Applications

Structured Knowledge: Expert systems use formal representations to organize and store knowledge in a structured manner. Then, it will allow to easy retrieval and updating of this information.

Capture of Expertise: Expert systems can capture and store the expertise of human experts, preserving it for future use and dissemination.

Consistency: Expert systems make decisions based on predefined rules and knowledge, ensuring consistency in decision-making. This consistency is certainly most valuable in such situations where human decision-makers are unable to influence by emotions or other external factors.

Continuous Operation: Expert systems can operate around the clock without fatigue or breaks, providing consistent and continuous support. This is especially beneficial in fields where timely decisions are crucial.

Easily Scalable: Expert systems can be easily replicated and scaled across different platforms or locations, allowing organizations to leverage expertise across a wide range of situations.

Reduced Human Error: By getting automating decision-making processes; expert systems also allow to reduce the likelihood of human errors that can be critical in fields, including healthcare, manufacturing, and finance.

Training Tool: Expert systems are also able to deliver the valuable training tools that allow helping individuals for learning and understanding complex subjects by making the interacting with a system that easy to make emulate the decision-making processes of the expert.

Cost-Effective: In the long run, expert systems can lead to cost savings by reducing the need for human experts in routine or repetitive tasks, allowing organizations to allocate resources more efficiently.

Rapid Decision Making: Expert systems can analyse large amounts of data quickly and make decisions in real-time. This also can be implemented in crucial situations; whereas timely responses are essential, like as in emergency cases.

Knowledge Preservation: Expert systems provide a means to preserve and transfer knowledge from experienced individuals to a wider audience, especially as experts retire or move on.

Adaptable to Changes: Expert systems can be updated and modified easily to accommodate changes in knowledge or environmental factors, ensuring that the system remains relevant and effective over time.

Other Expert System Advantages Are:

  • Enhance delicious quality.
  • Reduces the cost of consulting an expert for solving the problem.
  • Provide a quick and efficient solution to a problem.
  • Offers high reliability.
  • It can tackle a very complex problem that is difficult for a human expert to solve.
  • Gathers scare expertise and use it efficiently.
  • Consistency – they provide consistent answers for repetitive decisions.
  • The expert system is available 24/7 and is never on holiday or off sick when needed.
  • The computer uses all the information it has, unlike a human expert who may forget and make mistakes.
  • Capture expertise before it is lost.
  • Reduce dependence upon one expert.
  • Reduce/eliminate error and inconsistency.
  • Allow non-experts to reach scientifically supportable conclusions.
  • Knowledge sharing
  • Automation and improve decisions.
  • Dissemination expertise and normalization decisions.

Disadvantages of Expert System

There are some limitations of expert system in various areas such as:

Click Here – Components and Architecture of Expert System

Narrow Focus: Expert systems are typically designed for a specific domain or problem. They may lack the versatility and broad understanding that a human expert might possess, limiting their applicability to a narrow range of tasks.

Challenges in Tacit Knowledge Capture: Expert systems may struggle to capture the implicit or experiential knowledge that human experts possess. Tacit knowledge, which is often based on intuition and experience, is challenging to formalize and represent in a rule-based system.

Rigid Decision Making: Expert systems rely on predefined rules and may struggle with situations that require flexibility, creativity, or a common-sense understanding of context, as these aspects are challenging to codify.

Accuracy of Knowledge Base: The effectiveness of an expert system is highly dependent on the accuracy and completeness of the knowledge base. If the knowledge base is out dated or contains inaccuracies, the system’s performance may be compromised.

Continuous Updating: Expert systems require regular updates to stay relevant and effective. Keeping the knowledge base up-to-date can be resource-intensive and may require on-going efforts from domain experts.

Limited Learning Capability: Expert systems may lack the ability to learn from experience or adapt to changing conditions without manual intervention. This limits their ability to improve over time based on feedback or new data.

Limited Handling of Uncertainty: Expert systems may struggle with situations characterized by uncertainty, ambiguity, or incomplete information. Human experts often excel in dealing with such scenarios, drawing on intuition and judgment.

High Initial Costs: Developing and implementing expert systems can be expensive, particularly in terms of the initial investment required for knowledge acquisition, system development, and training.

User Acceptance: Users may be resistant to relying solely on automated systems, especially in critical decision-making processes. Trust in the system’s capabilities may take time to build.

Potential for Bias: If the knowledge base reflects biases present in the data used for training, expert systems can perpetuate or exacerbate existing biases. Ensuring fairness and addressing ethical concerns is a challenge.

Challenges in Dynamic Environments: Expert systems may struggle to adapt to rapidly changing environments or situations where the rules and conditions are constantly evolving.

Other Expert System Disadvantages Are:

  • Taken more time
  • Higher Consumption
  • Not flexible
  • No having common sense
  • Having more bugs in its programs
  • Not able to adapt to altering environments
  • Difficult to maintain
  • Having legal and ethical areas
  • More expensive in development area
  • Having narrow focus
  • Required ground verification
  • No capable to process for complex automation
  • Require update manually
  • Development for specific domain

Characteristics of Expert System

There are several feature and characteristics of expert system in artificial intelligence.

  • Better reliable compare to human expert
  • Better explanation ability like as human expert’s capability.
  • Expert system has adequate response time that means it is capable to perform any task with in small time period, compare to human expert to chase the target point.
  • Symbolic representations is used for knowledge (rules, networks or frames), and it is able to execute their inference with using of symbolic computations which is closed resemble computations of natural language.
  • Expert system has to link with metaknowledge that means it is known about themselves with own knowledge limitations and abilities. Due to implementation of metaknowledge, it makes more interactive and simple for several data representations.
  • Expert system has better expert knowledge, so it is able to deliver accurate solution with applying of its knowledge.
  • Expert system is very domain specific like as diagnostic expert system is designed to troubleshoot computers, and it is able to perform all activities like as human expert.
  • Expert system is able to justify reasoning that means, it allows you to ask expert system for justifying its generated solution otherwise suggestion provided by it. Expert system offers to users entire rules and facts for using to chase their answers.
  • Expert system is able to explain that how to solve any specific by it, and due to this, user’s confidence is getting high.
  • Expert system is designed with using special programming languages like as LISP and PROLOG. These coding languages are simpler for addition, elimination or substitution with using of current rules and memory management abilities. These programming languages are offering few advantages to expert system such as – mix of integer and real variables, better memory management procedures, Extensive data manipulation routines, Incremental compilation, Tagged memory architecture, and more.
  • Human experts like as perishable but other side of expert system like as permanent.
  • It is capable to distribute the human’s expertise.
  • It has less cost of consulting an expert for several domains like as diagnostic expert system.
  • Expert system has higher level of expertise, so it is able to solve any problem with better efficiency and accuracy.
  • Better flexibility to solution of all problems.
  • Separates knowledge from control
  • Focuses expertise
  • Reasons heuristically
  • Limited to solvable problems

Wrapping Up

Now, we can hope that you have been fully educated about various advantages and disadvantages of expert system as well as characteristics of expert system in artificial intelligence with ease. If this post is helpful for you, then please share it along with your friends, family members or relatives over social media platforms like as Facebook, Instagram, Linked In, Twitter, and more.

Click Here – What is Fuzzy logic Controller? Applications and Examples!!

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