Logic Negation with Spiking Neural P Systems

被引：0
作者：
Daniel Rodríguez-Chavarría
Miguel A. Gutiérrez-Naranjo
Joaquín Borrego-Díaz
机构：
[1] University of Seville,Department of Computer Science and Artificial Intelligence
来源：
Neural Processing Letters | 2020年 / 52卷
关键词：
P systems; Logic negation; Membrane computing;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Nowadays, the success of neural networks as reasoning systems is doubtless. Nonetheless, one of the drawbacks of such reasoning systems is that they work as black-boxes and the acquired knowledge is not human readable. In this paper, we present a new step in order to close the gap between connectionist and logic based reasoning systems. We show that two of the most used inference rules for obtaining negative information in rule based reasoning systems, the so-called Closed World Assumption and Negation as Finite Failure can be characterized by means of spiking neural P systems, a formal model of the third generation of neural networks born in the framework of membrane computing.
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页码：1583 / 1599
页数：16
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