Forward chaining

This article is not adequately provided with supporting documents (for example individual proofs ). Information without sufficient evidence could be removed soon. Please help Wikipedia by researching the information and including good evidence.

Information must be substantiated by reputable sources of information in the article itself. It is not sufficient to mention presentation slides in the summary line.

As a forward chaining (engl .: forward chaining or forward reasoning ) is called a strategy of linking rules in a system for deriving a logical inferences, a so-called inference engine . On the basis of a rule that is in the form

wenn Faktum, dann Folgerung

is represented, a simple conclusion can be drawn. Often, however, one wants to draw more complex conclusions from several given rules. One way of doing this is to chain rules together. The forward chaining is transitive , i.e. H. A conclusion is drawn from a fact using a rule and an inference method (e.g. modus ponens ), which in turn is used as a premise and a further rule for a further conclusion, etc. Since a mostly case-specific fact is assumed, one designates this inference strategy also as data-driven inference .

A related inference strategy is backward chaining .

Example of a forward chaining rule interpreter

Working memory: X, Y, Z

Standard knowledge base:

1. X, Y -> S
2. S, Z -> T
3. S, Y -> A
4. Y, T -> B
5. X, T -> C

Goal: C is in memory

Conflict resolution:

1. Ignore rules that add symbols that are already in memory again
2. Consider rules according to their order in the rule memory

Possible solution:

step	random access memory	applied rule
1	X, Y, Z	X, Y -> S (rule 1)
2	X, Y, Z, S	S, Z -> T (rule 2)
3	X, Y, Z, S, T	S, Y -> A (rule 3)
4th	X, Y, Z, S, T, A	Y, T -> B (rule 4)
5	X, Y, Z, S, T, A, B	X, T -> C (rule 5)
6th	X, Y, Z, S, T, A, B, C	(Goal achieved)