Investigating Fitness Measures for the Automatic Construction of Graph Models

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{Harrison:2015:evoApplications,

• author = "Kyle Harrison and Mario Ventresca and Beatrice Ombuki-Berman",
• title = "Investigating Fitness Measures for the Automatic Construction of Graph Models",
• booktitle = "18th European Conference on the Applications of Evolutionary Computation",
• year = "2015",
• editor = "Antonio M. Mora and Giovanni Squillero",
• series = "LNCS",
• volume = "9028",
• publisher = "Springer",
• pages = "189--200",
• address = "Copenhagen",
• month = "8-10 " # apr,
• organisation = "EvoStar",
• keywords = "genetic algorithms, genetic programming, Complex networks, Graph models, Centrality measures, Meta-analysis:poster",
• isbn13 = "978-3-319-16548-6",
• DOI = "doi:10.1007/978-3-319-16549-3_16",
• abstract = "Graph models are often constructed as a tool to better understand the growth dynamics of complex networks. Traditionally, graph models have been constructed through a very time consuming and difficult manual process. Recently, there have been various methods proposed to alleviate the manual efforts required when constructing these models, using statistical and evolutionary strategies. A major difficulty associated with automated approaches lies in the evaluation of candidate models. To address this difficulty, this paper examines a number of well-known network properties using a proposed meta-analysis procedure. The meta-analysis demonstrated how these network measures interacted when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results formed the basis of a fitness evaluation scheme used in a genetic programming (GP) system to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce two well-known graph models, the results of which indicated that the evolved models exemplified striking similarity when compared to their respective targets on a number of structural network properties.",
• notes = "EvoCOMPLEX EvoApplications2015 held in conjunction with EuroGP'2015, EvoCOP2015 and EvoMusArt2015 http://www.evostar.org/2015/cfp_evoapps.php",

}

Genetic Programming entries for Kyle Robert Harrison Mario Ventresca Beatrice Ombuki-Berman

Citations