Abstract—Nowadays, more and more students all over the
world need expert systems, especially in academic sectors. They
need advice in order to be successful in their studies, and this
advice must be provided by the academic management. There
are two reasoning strategies in expert system, which have
become the major practical application of artificial intelligence
research: forward chaining and backward chaining. The first
one starts from the available facts and attempts to draw
conclusions about the goal. The second strategy starts from
expectations of what the goal is, and then attempts to find
evidence to support these hypotheses. The aim of this paper is
to make a comparative study to identify which reasoning
strategy system (forward chaining or backward chaining) is
more applicable when making evaluations in expert
management, especially in the academic field.
Index Terms—Artificial intelligence, expert system, forward
and backward chaining, state space.
Ajlan Al-Ajlan is with the Department of Information System
Management, Qassim University, Saudi Arabia (e-mail:
aajlan@qu.edu.com).
Cite: Ajlan Al-Ajlan, "The Comparison between Forward and Backward Chaining," International Journal of Machine Learning and Computing vol. 5, no. 2, pp. 106-113, 2015.