Editing Forward chaining (section)

==Example==

Suppose that the goal is to conclude the color of a pet named Fritz, given that he croaks and eats flies, and that the [[rule base]] contains 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 blue

Let us illustrate forward chaining by following the pattern of a computer as it evaluates the rules.
Assume the following facts:
* Fritz croaks
* Fritz eats flies

With forward reasoning, the inference engine can derive that Fritz is green in a series of steps:

1. Since the base facts indicate that "Fritz croaks" and "Fritz eats flies", the antecedent of rule #1 is satisfied by substituting Fritz for ''X'', and the inference engine concludes:
  Fritz is a frog

2. The antecedent of rule #3 is then satisfied by substituting Fritz for ''X'', and the inference engine concludes:
  Fritz is green

The name "forward chaining" comes from the fact that the inference engine starts with the data and reasons its way to the answer,
as opposed to [[backward chaining]], which works the other way around.
In the derivation, the rules are used in the opposite order as compared to [[backward chaining]].
In this example, rules #2 and #4 were not used in determining that Fritz is green.

Because the data determines which rules are selected and used, this method is called [[data-driven science|data-driven]], in contrast to [[goal-oriented|goal-driven]] [[backward chaining]] inference. The forward chaining approach is often employed by [[expert system]]s, such as [[CLIPS]].

One of the advantages of forward-chaining over backward-chaining is that the reception of new data can trigger new inferences, which makes the engine better suited to dynamic situations in which conditions are likely to change.<ref name="Hayes-Roth 1983">{{cite book|last=Hayes-Roth|first=Frederick|title=Building Expert Systems|year=1983|publisher=Addison-Wesley|isbn=0-201-10686-8|author2=Donald Waterman|author3=Douglas Lenat|url-access=registration|url=https://archive.org/details/buildingexpertsy00temd}}</ref><ref>{{cite web|last=Kaczor|first=Krzystof|title=Overview of Expert System Shells|url=https://home.agh.edu.pl/~ligeza/wiki/lib/exe/fetch.php?media=ke:ruleinfalg.pdf|work=geist.agh.edu.pl/|publisher=Institute of Automatics: AGH University of Science and Technology, Poland|access-date=5 December 2013|author2=Szymon Bobek |author3=Grzegorz J. Nalepa |location=Krakow, Poland|date=2010-12-05}}</ref>