Backward chaining is one of the two main methods of reasoning when using inference rules. The other is forward chaining. Reasoning is the mental (cognitive) process of looking for reasons to support beliefs, conclusions, actions or feelings. ... In logic, especially in mathematical logic, a rule of inference is a scheme for constructing valid inferences. ... Forward chaining is one of the two main methods of reasoning when using inference rules (in artificial intelligence). ...

Backward chaining starts with a list of goals (or a hypothesis) and works backwards to see if there is data available that will support any of these goals. An inference engine using backward chaining would search the inference rules until it finds one which has a Then clause that matches a desired goal. If the If clause of that inference rule is not known to be true, then it is added to the list of goals (in order for your goal to be confirmed you must also provide data that confirms this new rule). An objective or goal is a personal or organizational desired end point in development. ... Look up Hypothesis in Wiktionary, the free dictionary. ... For other uses, see Data (disambiguation). ... An inference engine tries to derive answers from a knowledge base. ... Inference is the act or process of deriving a conclusion based solely on what one already knows. ...

For example, suppose that the goal is to conclude the color of my pet Fritz, given that he croaks and eats flies, and that the rulebase contains the following four rules:

1. If Fritz croaks and eats flies - Then Fritz is a frog
2. If Fritz chirps and sings - Then Fritz is a canary
3. If Fritz is a frog - Then Fritz is green
4. If Fritz is a canary - Then Fritz is yellow

This rulebase would be searched and the third and fourth rules would be selected, because their conclusion (the Then clause) matches the goal (to determine Fritz's color). It is not yet known that Fritz is a frog, so the If statements are added to the goal list. The rulebase is again searched and this time the first two rules are selected, because their Then clauses match the new goals that were just added to the list (whether Fritz is a frog or whether Fritz is a canary). The If clause (Fritz croaks and eats flies) is known to be true and therefore it can be concluded that Fritz is a frog, and not a canary. The goal of determining Fritz's color is now achieved (Fritz is green if he is a frog, and yellow if he is a canary, but since he croaks and eats flies, he is a frog, and, therefore, he is green).

Because the list of goals determines which rules are selected and used, this method is called goal driven, in contrast to data-driven forward-chaining inference. The bottom-up approach of backward chaining is often employed by expert systems. A system, person, or organization that tends to achieve a goal and demonstrate it in subsequent actions. ... Eager evaluation or strict evaluation is the evaluation strategy in most traditional programming languages. ... An expert system is a class of computer programs developed by researchers in artificial intelligence during the 1970s and applied commercially throughout the 1980s. ...

Programming languages such as Prolog, Knowledge Machine and ECLiPSe support backward chaining. Prolog is a logic programming language. ... The Knowledge Machine is a concept of Dr. Papert, which is intended to enable children to explore any situation and engage them completely. ... This article is about astronomical eclipses. ...

See Also

• Forward chaining