Rule Engine -backward chaining
0 likes427 views
Backward chaining is a method of reasoning that works backward from a goal to determine if the goal can be proven true based on available information. It assumes a goal and works to find rules and facts that support that goal. For example, if the goal is to determine if a new pet Fritz is green, it can be proven in four steps by applying rules: 1) Fritz croaks and eats flies, so by rule 1 Fritz is a frog, 2) if Fritz is a frog then by rule 3 Fritz is green, thus proving the goal that Fritz is green. Backward chaining is useful for goal-driven and diagnostic applications where the goal is to determine if a hypothesis can be supported through available data.
Rule Engine -backward chaining
- 1. Working of - Backward Chaining Backward Chaining: • Is an inference method that can be described (in lay terms) as working backward from the goal(s). • It is used in automated theorem proofs, inference engines, proof assistants and other artificial intelligence applications. • Described as working backward for goals (Backward Reasoning) How it works ?? Assume a new pet, Fritz, is delivered in an opaque box along with two facts about Fritz: The goal is to decide whether Fritz is green, based on a rule base containing the following four rules: • If X croaks and X eats flies – Then X is a frog • If X chirps and X sings – Then X is a canary • If X is a frog – Then X is green • If X is a canary – Then X is yellow An inference engine can determine whether Fritz is green in four steps as shown on right side. This derivation therefore allows the inference engine to prove that Fritz is green. Rules #2 & #4 were not used. Applications: • Event driven systems are a common application of forward chain engines. • One example of a forward chaining application might be a teleco provisioning engine (typically used for administering mobile phon Entering a particular user with a particular plan will trigger a range of Significance of Backward Chaining: • Diagnosis • Goal Driven • Top down reasoning(hypothesis) • Find facts that support hypothesis