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Artículo
Semantics of deductive databases with spiking neural P systems
Autor/es | Díaz Pernil, Daniel
Gutiérrez Naranjo, Miguel Ángel |
Departamento | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII) |
Fecha de publicación | 2018 |
Fecha de depósito | 2018-04-09 |
Publicado en |
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Resumen | The integration of symbolic reasoning systems based on logic and connectionist systems based on thefunctioning of living neurons is a vivid research area in computer science. In the literature, one can findmany efforts ... The integration of symbolic reasoning systems based on logic and connectionist systems based on thefunctioning of living neurons is a vivid research area in computer science. In the literature, one can findmany efforts where different reasoning systems based on different logics are linked to classic artificialneural networks. In this paper, we study the relation between the semantics of reasoning systems basedon 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 nega- tion can be implemented in the spiking neural P systems model and such a model can also deal withnegation if it is endowed with anti-spikes and annihilation rules. |
Cita | Díaz Pernil, D. y Gutiérrez Naranjo, M.Á. (2018). Semantics of deductive databases with spiking neural P systems. Neurocomputing, 272 (January), 365-373. |
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