Expert system definition
An expert system is a branch of artificial intelligence (AI) that is designed to solve problems that otherwise would need a human with specific knowledge. It copies how a human would make decisions and gives advice or suggestions in specific areas.
Expert systems use two main parts to work: a knowledge base and an inference engine. The knowledge base is like a big library of information about a certain topic, while the inference engine applies logical rules to the knowledge base to deduce new information when needed. There’s also a dialogue interface that allows users to interact with the system.
One of the first and most famous expert systems was called MYCIN. It was created in the 1970s, and its job was to figure out what kind of bacteria was causing serious infections and suggest the right antibiotics. These days, we use expert systems in lots of areas. They help diagnose diseases, analyze financial records, understand voice commands, and even help self-driving cars navigate.
See also: artificial intelligence
Advantages of using expert systems
- Consistency: Expert systems offer consistent advice and avoid human errors caused by fatigue or oversight.
- Availability: They are available 24/7 and can be used in multiple places at once.
- Efficiency: They can process large amounts of data and deliver recommendations quickly.
Disadvantages of using expert systems
- Lack of common sense: Expert systems lack the ability to apply common sense and intuition that only humans have.
- Limited domain: They are restricted to their specific knowledge domain and cannot handle situations outside of it.
- Cost and maintenance: Developing and maintaining an expert system could require a lot of time and money
