Components of Expert System

Components of Expert System

  • User Interface
  • Inference Engine
  • Knowledge Base

1. User Interface

The expert system communicates with the user through a user interface, takes queries as input in a legible format, and delivers them to the inference engine. It displays the user's output after receiving the inference engine's response. In other words, it's a user interface that allows a non-expert user to communicate with an expert system to solve a problem.

2. Inference Engine(Rules of Engine)

  • Because it is the system's central processing unit, the inference engine is referred to as the "brain" of the expert system. It uses inference rules to derive conclusions or deduce new information from the knowledge base. It aids in deriving an error-free solution to the user's questions.
  • The system extracts knowledge from the knowledge base with the help of an inference engine.
  • Inference engines are divided into two types:
  • Engine for Deterministic Inference: This sort of inference engine's conclusions are assumed to be correct. It is founded on facts and regulations.
  • Probabilistic Inference Engine: This inference engine is based on probability and contains uncertainty in conclusions.

  • The following modes are used by the inference engine to generate solutions:

  • Forward Chaining: This method begins with known facts and rules, then applies inference rules to add their conclusions to the known facts.
  • Backward Chaining: This is a style of backward reasoning that begins with the aim and proceeds backwards to prove the known facts.

3. Knowledge Base

  • A knowledge base is storage that contains information gathered from various specialists on a specific topic. It is regarded as a large repository of knowledge. The Expert System will be more precise as the knowledge base grows.
  • It's akin to a database that stores data and rules for a specific topic or subject.
  • The knowledge base can alternatively be viewed as a collection of items and qualities. A lion, for example, is an item with the properties of being a mammal, not being a domestic animal, and so on.

  • Components of Knowledge Base

  • Factual Knowledge: Factual knowledge is the knowledge that is founded on facts and approved by knowledge engineers.
  • Heuristic Information: This knowledge is based on experience, the ability to guess, and evaluation.