Article
Logic Negation with Spiking Neural P Systems
Author/s | Rodríguez Chavarría, Daniel
Gutiérrez Naranjo, Miguel Ángel Borrego Díaz, Joaquín |
Department | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial |
Publication Date | 2020 |
Deposit Date | 2021-03-26 |
Published in |
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Abstract | 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. ... 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. |
Funding agencies | Ministerio de Ciencia, Innovación y Universidades (MICINN). España Ministerio de Ciencia, Innovación y Universidades (MICINN). España |
Project ID. | PID2019-109152GBI00
PID2019-107339GB-I00 |
Citation | Rodríguez Chavarría, D., Gutiérrez Naranjo, M.Á. y Borrego Díaz, J. (2020). Logic Negation with Spiking Neural P Systems. Neural Processing Letters, 52, 1583-1599. |
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