Evolving modules in Genetic Programming by subtree encapsulation

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@InProceedings{roberts:2001:EuroGP,

• author = "Simon C. Roberts and Daniel Howard and John R. Koza",
• title = "Evolving modules in Genetic Programming by subtree encapsulation",
• booktitle = "Genetic Programming, Proceedings of EuroGP'2001",
• year = "2001",
• editor = "Julian F. Miller and Marco Tomassini and Pier Luca Lanzi and Conor Ryan and Andrea G. B. Tettamanzi and William B. Langdon",
• volume = "2038",
• series = "LNCS",
• pages = "160--175",
• address = "Lake Como, Italy",
• publisher_address = "Berlin",
• month = "18-20 " # apr,
• organisation = "EvoNET",
• publisher = "Springer-Verlag",
• keywords = "genetic algorithms, genetic programming, Modularisation, Code Reuse, Subtree Encapsulation, Image Processing",
• ISBN = "3-540-41899-7",
• DOI = "doi:10.1007/3-540-45355-5_13",
• size = "16 pages",
• abstract = "In tree-based genetic programming (GP), the most frequent subtrees on later generations are likely to constitute useful partial solutions. This paper investigates the effect of encapsulating such subtrees by representing them as atoms in the terminal set, so that the subtree evaluations can be exploited as terminal data. The encapsulation scheme is compared against a second scheme which depends on random subtree selection. Empirical results show that both schemes improve upon standard GP.",
• notes = "EuroGP'2001, part of \cite{miller:2001:gp}",

}

Genetic Programming entries for Simon C Roberts Daniel Howard John Koza

Citations