What is an expert system?An expert system is a computer program that uses artificial intelligence (AI) technologies to simulate the judgment and behavior of a human or an organization that has expertise and experience in a particular field. Show
Expert systems are usually intended to complement, not replace, human experts. The concept of expert systems was developed in the 1970s by computer scientist Edward Feigenbaum, a computer science professor at Stanford University and founder of Stanford's Knowledge Systems Laboratory. The world was moving from data processing to "knowledge processing," Feigenbaum said in a 1988 manuscript. That meant computers had the potential to do more than basic calculations and were capable of solving complex problems thanks to new processor technology and computer architectures, he explained. How does an expert system work?Modern expert knowledge systems use machine learning and artificial intelligence to simulate the behavior or judgment of domain experts. These systems can improve their performance over time as they gain more experience, just as humans do. Expert systems accumulate experience and facts in a knowledge base and integrate them with an inference or rules engine -- a set of rules for applying the knowledge base to situations provided to the program. The inference engine uses one of two methods for acquiring information from the knowledge base:
An expert system relies on having a good knowledge base. Experts add information to the knowledge base, and nonexperts use the system to solve complex problems that would usually require a human expert. The process of building and maintaining an expert system is called knowledge engineering. Knowledge engineers ensure that expert systems have all the necessary information to solve a problem. They use various knowledge representation methodologies, such as symbolic patterns, to do this. The system's capabilities can be enhanced by expanding the knowledge base or creating new sets of rules. What are the components of an expert system?There are three main components of an expert system:
Applications of expert systemsExpert systems can be effective in specific domains or subject areas where experts are required to make diagnoses, judgments or predictions.
These systems have played a large role in many industries, including the following:
Examples of expert systemsExpert systems that are in use include the following examples:
Advantages of expert systemsExpert systems have several benefits over the use of human experts:
Challenges of expert systemsAmong expert systems' shortcomings are the following:
Expert systems require the use of AI to deal with ever growing data processing demands. Learn about hosting and implementing AI in the enterprise with this complete guide. This was last updated in July 2022 Continue Reading About expert system
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Which of the following is a computer based system that attempts to emulate?Artificial intelligence consists of computer-based systems that attempt to emulate human behavior, such as learning languages, accomplishing physical tasks (robotics), and emulate human decision-making. AI is the basis for many of the intelligent techniques involved in knowledge management.
Which of the following is a computer system that can simulate the functioning of a human brain?A neural network relies on massively parallel processing to enable a computer to simulate the function of a human brain.
Which of the following has a large number of sensing and processing nodes that continuously interact with each other?A neural net has a large number of sensing and processing nodes that continuously interact with each other. Figure 12-15 represents one type of neural network comprising an input layer, an output layer, and a hidden processing layer.
What is meant by knowledge is sticky?Knowledge stickiness can be defined as the difficulty to transfer knowledge.
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