Ponencia
Semantics of Deductive Databases in a Membrane Computing Connectionist Model
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 | 2016 |
Fecha de depósito | 2016-12-07 |
Publicado en |
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Resumen | 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 found many e orts ... 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 found many e orts where di erent reasoning systems based on di erent logics are linked to classic arti cial 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 xed point semantics of deductive databases and the immediate consequence operator can be implemented in the spiking neural P systems model. |
Cita | Díaz Pernil, D. y Gutiérrez Naranjo, M.Á. (2016). Semantics of Deductive Databases in a Membrane Computing Connectionist Model. En BWMC 2016 : 14th Brainstorming Week on Membrane Computing : Sevilla, E. T. S. de Ingeniería Informática, February 1-5 (173-184), Sevilla: Fénix. |
Ficheros | Tamaño | Formato | Ver | Descripción |
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173_dani_miguel_semantics.pdf | 269.0Kb | [PDF] | Ver/ | |