In Artificial Intelligence field, Knowledge Engineering phase is considered
the most crucial phase of the development life cycle of the Knowledge Base
Systems [1]. In fact, Formal Logic in general and Modus Ponens specifically has
been the dominan
t tools for structuring this knowledge [3]. This led for forming
a gap between the knowledge area and the information area, which depends
structurally on the Set Theory in general and on the Relational Algebra in
particular [1]. Thus, trying to introduce a bridge to pass this gap in structuring
and treating knowledge, we have conducted a new knowledge representation
model that depends structurally on (Classical and Fuzzy) Set Theory. Then we
used it as the base for conducting an inference model that attempt, using a set
of algebraic operations and by going through a series of stages, to reach a
solution of the problem under study, in a manner very close to the one that
humans usually use in treating their knowledge, taking into consideration the
speed and accuracy as much as the problem allows.
