Memetic Genetic Programming based on orthogonal projections in the phenotype space

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Graff:2015:ROPEC,

• author = "Mario Graff and Eric S. Tellez and Hugo Jair Escalante and Jose Ortiz-Bejar",
• booktitle = "2015 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)",
• title = "Memetic Genetic Programming based on orthogonal projections in the phenotype space",
• year = "2015",
• abstract = "Genetic Programming (GP) is an evolutionary algorithm that has received a lot of attention lately due to its success in solving hard real-world problems. Lately, there has been a great interest in GP's community to develop semantic genetic operators, i.e., operators that work on the phenotype. In this contribution, we improve the performance of GP by making orthogonal projections in the phenotype space using the behaviour of the parents and the target, i.e., the problem at hand. The technique proposed can be easily applied to any tree based GP, and, as the result show this technique statistically improves the performance of GP. Furthermore, we experimentally show how a traditional GP system enhanced with our technique can outperform the state of the art geometric semantic GP systems.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/ROPEC.2015.7395160",
• month = nov,
• notes = "Also known as \cite{7395160}",

}

Genetic Programming entries for Mario Graff Guerrero Eric Sadit Tellez Hugo Jair Escalante Jose Ortiz Bejar

Citations