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Grammatical evolution (GE) is an evolutionary computation and, more specifically, a genetic programming (GP) technique (or approach) pioneered by Conor Ryan, JJ Collins and Michael O'Neill in 1998 at the BDS Group in the University of Limerick.

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rdfs:label	Evolución gramatical (es) Grammatical evolution (en)
rdfs:comment	Grammatical evolution (GE) is an evolutionary computation and, more specifically, a genetic programming (GP) technique (or approach) pioneered by Conor Ryan, JJ Collins and Michael O'Neill in 1998 at the BDS Group in the University of Limerick. (en) La evolución gramatical es una técnica relativamente nueva de computación evolutiva iniciada por Conor Ryan, JJ Collins y Michael O'Neill en 1998 en el Grupo BD S en la Universidad de Limerick. Se relaciona con la idea de Programación Genética en que el objetivo es encontrar un programa ejecutable o fragmento de programa, que logre un buen valor de comportamiento para la función objetivo dada. En la mayoría de los trabajos publicados sobre la Programación Genética, una expresión en forma de árbol es estructurada al estilo LISP se maneja directamente, mientras que la Evolución gramatical aplica operadores genéticos (operador genético) a una cadena de números enteros, posteriormente asignada a un programa mediante el uso de una gramática. (es)
dcterms:subject	Evolutionary algorithms
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Link from a Wikipage to another Wikipage	University of Limerick Genetic operator Genetic programming Gene expression programming Multi expression programming Objective function John Koza Particle swarm optimization Backus-Naur form Backus–Naur form Linear genetic programming LISP Ecological stability Java Grammatical Evolution Evolutionary algorithms Bond credit rating Cartesian genetic programming R (programming language) Genetic algorithms Evolutionary computation Predator-prey model
Link from a Wikipage to an external page	http://bds.ul.ie/libGE/%3C/nowiki%3E http://geret.org/ http://ncra.ucd.ie/Site/GEVA.html%3C/nowiki%3E http://nohejl.name/age/pdf/AGE-Documentation-1.0.2.pdf%3C/nowiki%3E http://pyneurgen.sourceforge.net/%3C/nowiki%3E https://ritchielab.org/research/past-research/52-grammatical-evolution-neural-networks%3C/nowiki%3E https://web.archive.org/web/20101129085227/http:/www.bangor.ac.uk/~eep201/jge/ https://web.archive.org/web/20110721124315/http:/www.grammaticalevolution.org/tutorial.pdf https://web.archive.org/web/20161107073933/http:/drp.rubyforge.org/ https://code.google.com/archive/p/ponyge/downloads%3C/nowiki%3E http://lancet.mit.edu/ga/ https://cs.gmu.edu/~eclab/projects/ecj/%3C/nowiki%3E http://www.cleveralgorithms.com/nature-inspired/evolution/grammatical_evolution.rb%3C/nowiki%3E http://ncra.ucd.ie/geva http://bds.ul.ie http://www.grammatical-evolution.org http://www.ul.ie https://arxiv.org/abs/1703.08535%3C/nowiki%3E https://github.com/adilraja/GELAB%3C/nowiki%3E https://github.com/bver/GERET/%3C/nowiki%3E https://cran.r-project.org/web/packages/gramEvol/index.html https://cran.r-project.org/web/packages/gramEvol/vignettes/ge-intro.pdf%3C/nowiki%3E
sameAs	Grammatical evolution Grammatical evolution Grammatical evolution Grammatical evolution Grammatical evolution
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has abstract	Grammatical evolution (GE) is an evolutionary computation and, more specifically, a genetic programming (GP) technique (or approach) pioneered by Conor Ryan, JJ Collins and Michael O'Neill in 1998 at the BDS Group in the University of Limerick. As in any other GP approach, the objective is to find an executable program, program fragment, or function, which will achieve a good fitness value for a given objective function. In most published work on GP, a LISP-style tree-structured expression is directly manipulated, whereas GE applies genetic operators to an integer string, subsequently mapped to a program (or similar) through the use of a grammar, which is typically expressed in Backus–Naur form. One of the benefits of GE is that this mapping simplifies the application of search to different programming languages and other structures. (en) La evolución gramatical es una técnica relativamente nueva de computación evolutiva iniciada por Conor Ryan, JJ Collins y Michael O'Neill en 1998 en el Grupo BD S en la Universidad de Limerick. Se relaciona con la idea de Programación Genética en que el objetivo es encontrar un programa ejecutable o fragmento de programa, que logre un buen valor de comportamiento para la función objetivo dada. En la mayoría de los trabajos publicados sobre la Programación Genética, una expresión en forma de árbol es estructurada al estilo LISP se maneja directamente, mientras que la Evolución gramatical aplica operadores genéticos (operador genético) a una cadena de números enteros, posteriormente asignada a un programa mediante el uso de una gramática. Uno de los beneficios de Evolución Gramatical (GE) es que este mapeo simplifica la aplicación de la búsqueda a diferentes lenguajes de programación y otras estructuras. (es)
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is Link from a Wikipage to another Wikipage of	Genetic programming Gene expression programming Multi expression programming MOEA Framework Linear genetic programming Grammatical Evolution Java Grammatical Evolution Artificial development Cartesian genetic programming Evolutionary algorithm Evolutionary computation Outline of machine learning
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