The DU Map: A Visualization to Gain Insights into Genotype-phenotype Mapping and Diversity
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InProceedings{Medvet:2017:GECCOc,
-
author = "Eric Medvet and Tea Tusar",
-
title = "The {DU} Map: A Visualization to Gain Insights into
Genotype-phenotype Mapping and Diversity",
-
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 = "1705--1712",
-
size = "8 pages",
-
URL = "http://doi.acm.org/10.1145/3067695.3082554",
-
DOI = "doi:10.1145/3067695.3082554",
-
acmid = "3082554",
-
publisher = "ACM",
-
publisher_address = "New York, NY, USA",
-
keywords = "genetic algorithms, genetic programming, Grammatical
Evolution, diversity, genotype-phenotype mapping, heat
maps, redundancy, visualization",
-
month = "15-19 " # jul,
-
abstract = "The relation between diversity and genotype to
phenotype mapping has been the focus of several
studies. In those Evolutionary Algorithms (EAs) where
the genotype is a sequence of symbols, the contribution
of each of those symbols in determining the phenotype
may vary greatly possibly being null. In the latter
case, the unused portions of the genotype may host a
large amount of the population diversity. However,
reasoning on coarse-grained measures makes it hard to
validate such a claim and, more in general, to gain
insights into the interactions between
genotype-phenotype mapping and diversity. In this
paper, we propose a novel visualization which
summarizes in a single, compact heat map (the DU map),
three kinds of information: (a) how diverse are the
genotypes in the population at the level of single
symbols; (b) if and to what degree each individual
symbol in the genotype contributes to the phenotype;
(c) how the two previous measures vary during the
evolution. We experimentally verify the usefulness of
the DU map w.r.t. its primary goal and, more broadly,
when used to analyse different EA design options. We
apply it to Grammatical Evolution (GE) as it
constitutes an ideal test bed for the DU map, due to
the availability of different mapping functions.",
-
notes = "Also known as \cite{Medvet:2017:DMV:3067695.3082554}
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
Eric Medvet
Tea Tusar
Citations