Information Technology IT – 7 Expert systems | e-Consult

Forward Chaining: This method starts with known facts and applies the rules to derive new facts until a goal is reached or no more rules can be applied. It proceeds from the facts towards a conclusion. It's data-driven.

Backward Chaining: This method starts with a goal (hypothesis) and tries to find evidence (facts) that support it. It works backward from the goal to determine what additional information is needed. It's goal-driven.

Example of Forward Chaining: A medical diagnosis system might use forward chaining to determine potential diseases based on a patient's symptoms. If the system knows a patient has a fever (fact) and the rule "IF fever THEN suspect infection" (rule), it will infer a possible infection.

Example of Backward Chaining: A troubleshooting system for computer problems might use backward chaining. If the goal is to identify the cause of a system crash, the system will try to find rules that explain the crash and identify potential causes. It works backward from the potential cause to confirm or reject it.