Genetic Programming with Scale-Free Dynamics

Created by W.Langdon from gp-bibliography.bib Revision:1.8110

@InProceedings{Araseki:2013:EVOLVE,

• author = "Hitoshi Araseki",
• title = "Genetic Programming with Scale-Free Dynamics",
• booktitle = "EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV",
• year = "2013",
• editor = "Michael Emmerich and Andre Deutz and Oliver Schuetze and Thomas Baeck and Emilia Tantar and Alexandru-Adrian and Pierre {Del Moral} and Pierrick Legrand and Pascal Bouvry and Carlos A. Coello",
• volume = "227",
• series = "Advances in Intelligent Systems and Computing",
• pages = "277--291",
• address = "Leiden, Holland",
• month = jul # " 10-13",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-319-01127-1",
• DOI = "doi:10.1007/978-3-319-01128-8_18",
• abstract = "This paper describe a new selection method, named SFSwT (Scale-Free Selection method with Tournament mechanism) which is based on a scale-free network study. A scale-free selection model was chosen in order to generate a scale-free structure. The proposed model reduces computational complexity and improves computational performance compared with a previous version of the model. Experimental results with various benchmark problems show that performance of the SFSwT is higher than with other selection methods. In various fields, scale-free structures are closely related to evolutionary computation. Further, it was found through the experiments that the distribution of node connectivity could be used as an index of search efficiency.",

}

Genetic Programming entries for Hitoshi Araseki

Citations