Backward chaining

What is backward chaining?
Backward chaining is an inference method that is widely used in artificial intelligence, automated theorem provers, and evidence assistants. The backward chaining method can be described as working back from a target. Many programming languages support backward chaining in their inference engines.

The backward chaining is also known as backward backward calculation.

Backward chaining is used in logic programming through selective linear definite clause resolution. It is one of the most widely used methods of reasoning with inference rules and logical implications. Backward chaining works backwards from a list of targets to see if there is data to support them. An inference engine that uses backward chaining searches through the inference rules until it finds a rule with a consequence that meets the desired goal. If the ancestor of this rule is known to be false, the rule is added to the list of destinations so data can be found to confirm it.

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