BWMC2008. Brainstorming Week On Membrane Computing (6th. 2008. Sevilla)

URI permanente para esta colecciónhttps://hdl.handle.net/11441/34357

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A First Model for Hebbian Learning with Spiking Neural P Systems
(Fénix Editora, 2008) Gutiérrez Naranjo, Miguel Ángel; Pérez Jiménez, Mario de Jesús; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; Ministerio de Educación y Ciencia (MEC). España; Junta de Andalucía; Universidad de Sevilla. TIC193: Computación Natural
Spiking neural P systems and artificial neural networks are computational devices which share a biological inspiration based on the transmission of information among neurons. In this paper we present a first model for Hebbian learning in the framework of Spiking Neural P systems by using concepts borrowed from neuroscience and artificial neural network theory.
Graphics and P Systems: Experiments with JPLANT
(Fénix Editora, 2008) Rivero Gil, Elena; Gutiérrez Naranjo, Miguel Ángel; Pérez Jiménez, Mario de Jesús; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; Ministerio de Educación y Ciencia (MEC). España; Junta de Andalucía; Universidad de Sevilla. TIC193: Computación Natural
The hand-made graphical representation of the configuration of a P system becomes a hard task when the number of membranes and objects increases. In this paper we present a new software tool, called JPLANT, for computing and representing the evolution of a P system model with membrane creation.We also present some experiments performed with JPLANT and point out new lines for the research in computer graphics with membrane systems.
Sixth Brainstorming Week on Membrane Computing Sevilla, February 4–February 8, 2008 : RGNC REPORT 01/2008
(Fénix Editora, 2008) Díaz Pernil, Daniel; Graciani Díaz, Carmen; Gutiérrez Naranjo, Miguel Ángel; Paun, Gheorghe; Pérez Hurtado de Mendoza, Ignacio; Riscos Núñez, Agustín; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; Research Group on Natural Computing; Universidad de Sevilla. TIC193: Computación Natural
Solving Numerical NP-complete Problems by Spiking Neural P Systems with Pre–computed Resources
(Fénix Editora, 2008) Gutiérrez Naranjo, Miguel Ángel; Leporati, Alberto; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; Ministerio de Educación y Ciencia (MEC). España; Junta de Andalucía; Universidad de Sevilla. TIC193: Computación Natural
Recently we have considered the possibility of using spiking neural P systems for solving computationally hard problems, under the assumption that some (possibly exponentially large) pre-computed resources are given in advance. In this paper we continue this research line, and we investigate the possibility of solving numerical NP-complete problems such as Subset Sum. In particular, we first propose a semi–uniform family of spiking neural P systems in which every system solves a specified instance of Subset Sum. Then, we exploit a technique used to calculate Iterated Addition with boolean circuits to obtain a uniform family of spiking neural P systems in which every system is able to solve all the instances of Subset Sum of a fixed size. All the systems here considered are deterministic, but their size generally grows exponentially with respect to the instance size.
Solving the Partition Problem by Using Tissue-like P Systems with Cell Division
(Fénix Editora, 2008) Díaz Pernil, Daniel; Gutiérrez Naranjo, Miguel Ángel; Pérez Jiménez, Mario de Jesús; Riscos Núñez, Agustín; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; Ministerio de Educación y Ciencia (MEC). España; Junta de Andalucía; Universidad de Sevilla. TIC193: Computación Natural
Tissue-like P systems with cell division is a computing model in the framework of Membrane Computing that shares with the spiking neural P system model a similar biological inspiration. Namely, both models are based on the intercellular communication and cooperation between neurons, respectively. Due to this fact, in both models the devices have the same structure: a network of elementary units (cells in a tissue and interconnected neurons, respectively). Nonetheless, the two models are quite different. One of the differences is the ability of tissue-like P systems with cell division for increasing the number of cells during the computation. In this paper we exploit this ability and present a polynomial-time solution for the (NP-complete) Partition problem via a uniform family of such P systems.
Testing Einstein’s Formula on Brownian Motion Using Membrane Computing
(Fénix Editora, 2008) Gálvez Santisteban, Manuel A.; Gutiérrez Naranjo, Miguel Ángel; Ramírez Martínez, Daniel; Rivero Gil, Elena; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; Ministerio de Educación y Ciencia (MEC). España; Junta de Andalucía; Universidad de Sevilla. TIC193: Computación Natural
Brownian motion refers to erratic movements of small particles of solid matter suspended in a fluid and it is the basis of the development of many fractals found in Nature. In this paper we use the Membrane Computing model of P systems with membrane creation and the software tool JPLANT in order to check the Einstein’s theory on the Mean Square Displacement of Brownian motion.

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Examinando BWMC2008. Brainstorming Week On Membrane Computing (6th. 2008. Sevilla) por Autor "Gutiérrez Naranjo, Miguel Ángel"