Semantics of deductive databases with spiking neural P systems

The integration of symbolic reasoning systems based on logic and connectionist systems based on the functioning of living neurons is a vivid research area in computer science. In the literature, one can find many efforts where different reasoning systems based on different logics are linked to classic artificial neural networks. In this paper, we study the relation between the semantics of reasoning systems based on propositional logic and the connectionist model in the framework of membrane computing, namely, spiking neural P systems. We prove that the fixed point semantics of deductive databases without negation can be implemented in the spiking neural P systems model and such a model can also deal with negation if it is endowed with anti-spikes and annihilation rules.