Knowledge representation and reasoning based on FRSN P system

Spiking neural P systems are a new class of emerging and promising computing models, but so far their ability to deal with fuzzy knowledge representation and fuzzy reasoning is hardly ever studied. In this paper, we extend the works in [6] and present a fuzzy reasoning spiking neural P system (FRSN P system) model to express fuzzy knowledge in which rule neurons are divided into three sub-categories which just correspond to the types of fuzzy production rules in the knowledge base of a rule-based system. The new proposed model is more flexible and reasonable than the one we have presented before.