A Framework for the Empirical Analysis of Genetic Programming System Performance

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

@InCollection{Flasch:2012:GPTP,

• author = "Oliver Flasch and Thomas Bartz-Beielstein",
• title = "A Framework for the Empirical Analysis of Genetic Programming System Performance",
• booktitle = "Genetic Programming Theory and Practice X",
• year = "2012",
• series = "Genetic and Evolutionary Computation",
• editor = "Rick Riolo and Ekaterina Vladislavleva and Marylyn D. Ritchie and Jason H. Moore",
• publisher = "Springer",
• chapter = "11",
• pages = "155--169",
• address = "Ann Arbor, USA",
• month = "12-14 " # may,
• keywords = "genetic algorithms, genetic programming, Symbolic regression, Design of experiments, Sequential parameter optimisation, Reproducible research, Multi-objective optimisation",
• isbn13 = "978-1-4614-6845-5",
• URL = "http://dx.doi.org/10.1007/978-1-4614-6846-2_11",
• DOI = "doi:10.1007/978-1-4614-6846-2_11",
• abstract = "This chapter introduces a framework for statistically sound, reproducible empirical research in Genetic Programming (GP). It provides tools to understand GP algorithms and heuristics and their interaction with problems of varying difficulty. Following an approach where scientific claims are broken down to testable statistical hypotheses and GP runs are treated as experiments, the framework helps to achieve statistically verified results of high reproducibility.",
• notes = "part of \cite{Riolo:2012:GPTP} published after the workshop in 2013",

}

Genetic Programming entries for Oliver Flasch Thomas Bartz-Beielstein

Citations