Semantics of deductive databases with spiking neural P systems

NEUROCOMPUTING

卷:272

Article

Diaz-Pernil, Daniel¹  Gutierrez-Naranjo, Miguel A.² 

[1] Univ Seville, Dept Appl Math 1, CATAM Res Grp, Seville, Spain

[2] Univ Seville, Dept Comp Sci & Artificial Intelligence, Seville, Spain

关键词: Membrane computing;    P systems;    Neural-symbolic integration;   

DOI  :  10.1016/j.neucom.2017.07.007

来源: Elsevier

【 摘 要 】

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. (C) 2017 Elsevier B.V. All rights reserved.

【 授权许可】

Free