Semantic-based Local Search in Multiobjective Genetic Programming

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

@InProceedings{Dou:2017:GECCO,

• author = "Tiantian Dou and Peter Rockett",
• title = "Semantic-based Local Search in Multiobjective Genetic Programming",
• booktitle = "Proceedings of the Genetic and Evolutionary Computation Conference Companion",
• series = "GECCO '17",
• year = "2017",
• isbn13 = "978-1-4503-4939-0",
• address = "Berlin, Germany",
• pages = "225--226",
• size = "2 pages",
• URL = "http://doi.acm.org/10.1145/3067695.3076015",
• DOI = "doi:10.1145/3067695.3076015",
• acmid = "3076015",
• publisher = "ACM",
• publisher_address = "New York, NY, USA",
• keywords = "genetic algorithms, genetic programming, local search, model selection, multiobjective optimization, semantic-based genetic programming",
• month = "15-19 " # jul,
• abstract = "We report a series of experiments within a multiobjective genetic programming (GP) framework using semantic-based local GP search. We have made comparison with the Random Desired Operator (RDO) of Pawlak et al. and find that a standard generational GP followed by a carefully-designed single-objective GP implementing semantic-based local search yields results statistically comparable to those obtained with the RDO operator. The trees obtained with our GP-based local search technique are, however, around half the size of the trees resulting from the use of the RDO.",
• notes = "Also known as \cite{Dou:2017:SLS:3067695.3076015} GECCO-2017 A Recombination of the 26th International Conference on Genetic Algorithms (ICGA-2017) and the 22nd Annual Genetic Programming Conference (GP-2017)",

}

Genetic Programming entries for Tiantian Dou Peter I Rockett

Citations