Describe the components of expert system.

An expert system is an AI program that solves problems in a narrow domain at the level of a human expert, for example medical diagnosis (MYCIN). Its main components are:

1. Knowledge base: stores the domain knowledge, usually as IF–THEN rules and facts collected from experts. Example: IF fever AND rash THEN possible measles.
2. Inference engine: the "brain" of the system. It applies the rules to the known facts to draw conclusions, using forward chaining (from facts to conclusions) or backward chaining (from a goal back to the facts that support it).
3. Working memory (database): holds the facts about the current problem, such as the user's answers and intermediate conclusions.
4. User interface: lets the user ask questions and enter facts, usually in a question-and-answer form, and shows the results.
5. Explanation facility: explains how a conclusion was reached and why a question is being asked. This builds the user's trust.
6. Knowledge acquisition facility: helps the knowledge engineer and domain experts add, change and test rules without reprogramming the system.

User <-> User interface <-> Inference engine <-> Knowledge base
                 ^                 |
                 |                 v
        Explanation facility   Working memory
                                   ^
                                   |
                     Knowledge acquisition (expert, engineer)