Ponencia
Self-constructing Recognizer P Systems
Autor/es | Díaz Pernil, Daniel
Peña Cantillana, Francisco 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 | 2014 |
Fecha de depósito | 2016-01-26 |
Publicado en |
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ISBN/ISSN | 978-84-940056-4-0 |
Resumen | Usually, the changes produced in the membrane structure of a P system are
considered side effects. The output of the computation is encoded as a multiset placed in a
specific region and the membrane structure in the ... Usually, the changes produced in the membrane structure of a P system are considered side effects. The output of the computation is encoded as a multiset placed in a specific region and the membrane structure in the halting configuration is not considered important. In this paper we explore P systems where the target of the computation is the construction of a new membrane structure according its set of rules. The new membrane structure can be considered as the initial one of a new self-constructed P system. We focus on the self-construction of recognizer P systems and illustrates the definition with a study of the self-construction P systems working as decision trees for solving Machine Learning decision problems. |
Agencias financiadoras | Ministerio de Economía y Competitividad (MINECO). España |
Identificador del proyecto | info:eu-repo/grantAgreement/MINECO/TIN2012-37434 |
Ficheros | Tamaño | Formato | Ver | Descripción |
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137_id3_mc.pdf | 125.8Kb | [PDF] | Ver/ | |