Reasoning system

One of the key characteristics of an
expert system is the explanation facility. With this capability, an expert system
can explain how it arrives at its conclusions. The user can ask questions dealing
with the what, how, and why aspects of a problem. The expert system will then
provide the user with a trace of the consultation process, pointing out the key
reasoning paths followed during the consultation. Sometimes an expert system is
required to solve other problems, possibly not directly related to the specific
problem at hand, but whose solution will have an impact on the total problemsolving
process. The explanation facility helps the expert system to clarify and
justify why such a digression might be needed.
Forward Chaining :
This method involves checking the condition part of a rule to determine whether it
is true or false. If the condition is true, then the action part of the rule is also true. This
procedure continues until a solution is found or a dead end is reached. Forward chaining
is commonly referred to as data-driven reasoning. Further discussions of forward
chaining are presented in subsequent chapters.
Backward Chaining :
Backward chaining is the reverse of forward chaining. It is used to backtrack from a
goal to the paths that lead to the goal. Backward chaining is very good when all
outcomes are known and the number of possible outcomes is not large. In this case, a
goal is specified and the expert system tries to determine what conditions are needed to
arrive at the specified goal. Backward chaining is thus also called goal-driven.