The role of keeping

Cruz Echeandía, Marina de la; Martín Lázaro, Alba; Ortega de la Puente, Alfonso; Montaña Arnaiz, José Luis; Alonso González, César Luis

doi:10.5220/0003085403650368

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RoleKeepingSemantic.pdf (658.0Kb)

Identificadores

URI: https://hdl.handle.net/10902/28556

DOI: 10.5220/0003085403650368

ISBN: 978-989-8425-31-7

Fecha

2010

Derechos

Attribution-NonCommercial-NoDerivatives 4.0 International

Publicado en

ICEC 2010 : International Conference on Evolutionary Computation : proceedings : Valencia, Spain, 24-26 October 2010, Setúbal, SciTePress, 2010

Editorial

ScitePress, Science and Technology Publications, Lda

Enlace a la publicación

https://doi.org/10.5220/0003085403650368

Palabras clave

Grammar evolution

Attribute grammars

Christiansen grammars

Genetic programming

Straight-line programs

Symbolic regression

Resumen/Abstract

This paper is focused on two different approaches (previously proposed by the authors) that perform better than Genetic Programming in typical symbolic regression problems: straight-line program genetic programming (SLP-GP) and evolution with attribute grammars (AGE). Both approaches have different characteristics. One of themost important is that SLP-GP keeps semantic blocks invariant (the crossover operator always exchanges complete subexpressions). In this paper we compare both methods and study the possible effect on their performance of keeping these blocks invariant.

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