When an AI system uses forward chaining, it starts with a set of facts and then tries to derive new facts from them until it reaches a goal. Forward chaining is often used in expert systems, a computer programme that uses a set of rules to solve problems.
It is a strategy of an expert system to answer the question: “What canhappen next?”
Here, the Inference Engine follows the chain of conditions and derivations and finally deduces the outcome. It considers all the facts and rules and sorts them before concluding a solution. This strategy is followed for working on a conclusion, result, or effect.
=> For example, the prediction of share market status as an effect of changes in interest rates.
Backward Chaining
With this strategy, an expert system finds out the answer to the question: “Why this happened?”
On the basis of what has already happened, the Inference Engine tries to find out which conditions could have occurred in the past to lead to this result. This strategy is followed to determine the cause or reason. => For example: the diagnosis of blood cancer in humans.
