What is forward chAIning and backward chAIning in Artificial Intelligence?
Answers
Explanation:
. No. Forward Chaining Backward Chaining
1. Forward chaining starts from known facts and applies inference rule to extract more data unit it reaches to the goal. Backward chaining starts from the goal and works backward through inference rules to find the required facts that support the goal.
2. It is a bottom-up approach It is a top-down approach
3. Forward chaining is known as data-driven inference technique as we reach to the goal using the available data. Backward chaining is known as goal-driven technique as we start from the goal and divide into sub-goal to extract the facts.
4. Forward chaining reasoning applies a breadth-first search strategy. Backward chaining reasoning applies a depth-first search strategy.
5. Forward chaining tests for all the available rules Backward chaining only tests for few required rules.
6. Forward chaining is suitable for the planning, monitoring, control, and interpretation application. Backward chaining is suitable for diagnostic, prescription, and debugging application.
7. Forward chaining can generate an infinite number of possible conclusions. Backward chaining generates a finite number of possible conclusions.
8. It operates in the forward direction. It operates in the backward direction.
9. Forward chaining is aimed for any conclusion. Backward chaining is only aimed for the required data.