Hierarchical Grammatical Evolution

author = "Eric Medvet",

title = "Hierarchical Grammatical Evolution",

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 = "249--250",

size = "2 pages",

URL = "

http://doi.acm.org/10.1145/3067695.3075972",

DOI = "

doi:10.1145/3067695.3075972",

acmid = "3075972",

publisher = "ACM",

publisher_address = "New York, NY, USA",

keywords = "genetic algorithms, genetic programming, Grammatical Evolution, genotype-phenotype mapping, locality, redundancy, representation",

month = "15-19 " # jul,

abstract = "We present Hierarchical Grammatical Evolution (HGE) and its variant Weighted HGE (WHGE), two novel genotype-phenotype mapping procedures to be used in the Grammatical Evolution (GE) framework. HGE/WHGE are designed to exhibit better variational inheritance than standard GE without imposing any constraint on the structure of the genotype nor on the genetic operators. Our proposal considers the phenotype as a hierarchy of non-terminal expansions and is based on two key ideas: (i) the closer the non-terminal to be expanded to the root of the hierarchy the larger the genotype substring determining its expansion, and (ii) upon expansion, a non-terminal divides its genotype sub-string among the resulting non-terminals. We experimentally evaluate our proposals on a set of benchmark problems and show that for the majority of them WHGE outperforms GE (and its variant πGE).",

notes = "Also known as \cite{Medvet:2017:HGE:3067695.3075972} GECCO-2017 A Recombination of the 26th International Conference on Genetic Algorithms (ICGA-2017) and the 22nd Annual Genetic Programming Conference (GP-2017)",