What are the three main components of an Expert System?

An Expert System is a type of artificial intelligence application that emulates the decision-making ability of a human expert. The three main components of an Expert System are the Knowledge Base, Inference Engine, and User Interface.

The Knowledge Base is integral because it contains all the facts and rules about a specific domain. This is where the system's expertise is stored, allowing it to provide informed advice or solutions based on the information contained within. The richness and accuracy of the Knowledge Base directly influence the effectiveness of the Expert System.

The Inference Engine acts as the brain of the system. It processes the information from the Knowledge Base and applies logical rules to derive conclusions or make decisions based on user inputs. The inference engine enables the system to perform reasoning, drawing upon the knowledge to manipulate data and derive results, much like a human would in a comparable situation.

Lastly, the User Interface is how users interact with the Expert System. A good user interface allows users to input queries easily and understand the outputs provided by the system, making it essential for usability and acceptance.

Together, these three components — the Knowledge Base, Inference Engine, and User Interface — enable the Expert System to function effectively, providing users with valuable insights and support in decision-making processes.