Backward Chaining Backward chaining (or backward reasoning) is an inference method used in automated theorem provers, proof assistants and other artificial intelligence applications. Backward chaining is implemented in logic programming by SLD resolution.
Backward chaining starts with a list of goals (or a hypothesis) and works backwards from the consequent to the antecedent to see if there is data available that will support any of these consequents. The backward chaining approach is often employed by expert systems.
Programming languages such as Prolog, Knowledge Machine and ECLiPSe support backward chaining within their inference engines.
