Quantitative Analysis of Locally Geometric Semantic Crossover

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Krawiec:2012:PPSN,

• author = "Krzysztof Krawiec and Tomasz Pawlak",
• title = "Quantitative Analysis of Locally Geometric Semantic Crossover",
• booktitle = "Parallel Problem Solving from Nature - PPSN XII",
• year = "2012",
• editor = "Carlos A. {Coello Coello} and Vincenzo Cutello and Kalyanmoy Deb and Stephanie Forrest and Giuseppe Nicosia and Mario Pavone",
• volume = "7491",
• series = "Lecture Notes in Computer Science",
• pages = "397--406",
• address = "Taormina, Italy",
• month = sep # " 1-5",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, semantic crossover, homology",
• isbn13 = "978-3-642-32936-4",
• URL = "http://dx.doi.org/10.1007/978-3-642-32937-1_40",
• DOI = "doi:10.1007/978-3-642-32937-1_40",
• abstract = "We investigate the properties of locally geometric semantic crossover (LGX), a genetic programming search operator that is approximately semantically geometric on the level of homologous code fragments. For a pair of corresponding loci in the parents, LGX finds a semantically intermediate procedure from a library prepared prior to evolutionary run, and creates an offspring by using such procedure as replacement code. LGX proves superior when compared to standard subtree crossover and other control methods in terms of search convergence, test-set performance, and time required to find a high-quality solution. This paper focuses in particular the impact of homology and program semantic on LGX performance.",
• notes = "PPSN-XII",

}

Genetic Programming entries for Krzysztof Krawiec Tomasz Pawlak

Citations