What Bloat? Cartesian Genetic Programming on Boolean Problems

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{miller:2001:wbcgpbp,

• author = "Julian Miller",
• title = "What Bloat? Cartesian Genetic Programming on {Boolean} Problems",
• booktitle = "2001 Genetic and Evolutionary Computation Conference Late Breaking Papers",
• year = "2001",
• editor = "Erik D. Goodman",
• pages = "295--302",
• address = "San Francisco, California, USA",
• month = "9-11 " # jul,
• keywords = "genetic algorithms, genetic programming, cartesian genetic programming, bloat, graph-based genetic programming, genotype-phenotype",
• URL = "http://www.elec.york.ac.uk/intsys/users/jfm7/gecco2001Late.pdf",
• abstract = "This paper presents an empirical study of the variation of program size over time, for a form of Genetic Programming called Cartesian Genetic Programming. Two main types of Cartesian genetic programming are examined: one uses a fully connected graph, with no redundant nodes, while the other allows partial connectedness and has redundant nodes. Studies are reported here for fitness based search and for a flat fitness landscape. The variation of program size with generation does not behave in a similar way to that reported in other studies on standard Genetic Programming. Depending on the form of Cartesian genetic programming, it is found that there is either very weak program bloat or zero bloat. It is argued that an important factor in the analysis of the change of program length is neutral drift, and that if genotype redundancy is present, the genetic neutral drift simultaneously improves search and compresses program code.",
• notes = "GECCO-2001LB",

}

Genetic Programming entries for Julian F Miller

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