Forward chaining vs Backward chaining | Difference between Forward chaining vs Backward chaining

Forward chaining.

1. It is also known as data driven inference technique.
2. Forward chaining matches the set of conditions and infer results from these conditions. Basically, forward chaining starts from a new data and aims for any conclusion.
3. It is bottom up reasoning.
4. It is a breadth first search.
5. It continues until no more rules can be applied or some cycle limit is met.
6. For example: If it is cold then I will wear a sweater. Here “it is cold is the data” and “I will wear a sweater”is a decision. It was already known that it is cold that is why it was decided to wear a sweater, This process is forward chaining.
7. It is mostly used in commercial applications i.e event driven systems are common example of forward chaining.
8. It can create an infinite number of possible conclusions.

Backward chaining.

1. It is also called as goal driven inference technique.
2. It is a backward search from goal to the conditions used to get the goal. Basically it starts from possible conclusion or goal and aims for necessary data.
3. It is top down reasoning.
4. It is a depth first search.
5. It process operations in a backward direction from end to start, it will stop when the matching initial condition is met.
6. For example: If it is cold then I will wear a sweater. Here we have our possible conclusion “I will wear a sweater”. If I am wearing a sweater then it can be stated that it is cold that is why I am wearing a sweater. Hence it was derived in a backward direction so it is the process of backward chaining.
7. It is used in interrogative commercial applications i.e finding items that fulfill possible goals.
8. Number of possible final answers is reasonable.

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