Asynchronously evolving solutions with excessively different evaluation time by reference-based evaluation
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{Harada:2014:GECCO,
-
author = "Tomohiro Harada and Keiki Takadama",
-
title = "Asynchronously evolving solutions with excessively
different evaluation time by reference-based
evaluation",
-
booktitle = "GECCO '14: Proceedings of the 2014 conference on
Genetic and evolutionary computation",
-
year = "2014",
-
editor = "Christian Igel and Dirk V. Arnold and
Christian Gagne and Elena Popovici and Anne Auger and
Jaume Bacardit and Dimo Brockhoff and Stefano Cagnoni and
Kalyanmoy Deb and Benjamin Doerr and James Foster and
Tobias Glasmachers and Emma Hart and Malcolm I. Heywood and
Hitoshi Iba and Christian Jacob and Thomas Jansen and
Yaochu Jin and Marouane Kessentini and
Joshua D. Knowles and William B. Langdon and Pedro Larranaga and
Sean Luke and Gabriel Luque and John A. W. McCall and
Marco A. {Montes de Oca} and Alison Motsinger-Reif and
Yew Soon Ong and Michael Palmer and
Konstantinos E. Parsopoulos and Guenther Raidl and Sebastian Risi and
Guenther Ruhe and Tom Schaul and Thomas Schmickl and
Bernhard Sendhoff and Kenneth O. Stanley and
Thomas Stuetzle and Dirk Thierens and Julian Togelius and
Carsten Witt and Christine Zarges",
-
isbn13 = "978-1-4503-2662-9",
-
pages = "911--918",
-
keywords = "genetic algorithms, genetic programming",
-
month = "12-16 " # jul,
-
organisation = "SIGEVO",
-
address = "Vancouver, BC, Canada",
-
URL = "http://doi.acm.org/10.1145/2576768.2598330",
-
DOI = "doi:10.1145/2576768.2598330",
-
publisher = "ACM",
-
publisher_address = "New York, NY, USA",
-
abstract = "The asynchronous evolution has an advantage when
evolving solutions with excessively different
evaluation time since the asynchronous evolution
evolves each solution independently without waiting for
other evaluations, unlike the synchronous evolution
requires evaluations of all solutions at the same time.
As a novel asynchronous evolution approach, this paper
proposes Asynchronous Reference-based Evaluation (ARE)
that asynchronously selects good parents by the
tournament selection using reference solution in order
to evolve solutions through a crossover of the good
parents. To investigate the effectiveness of ARE in the
case of evolving solutions with excessively different
evaluation time, this paper applies ARE to Genetic
Programming (GP), and compares GP using ARE (ARE-GP)
with GP using (mu+lambda) selection ((mu+lambda)-GP) as
the synchronous approach in particular situation where
the evaluation time of individuals differs from each
other. The intensive experiments have revealed the
following implications: (1) ARE-GP greatly outperforms
(mu+lambda)-GP from the viewpoint of the elapsed unit
time in the parallel computation environment, (2)
ARE-GP can evolve individuals without decreasing the
searching ability in the situation where the computing
speed of each individual differs from each other and
some individuals fail in their execution.",
-
notes = "Also known as \cite{2598330} GECCO-2014 A joint
meeting of the twenty third international conference on
genetic algorithms (ICGA-2014) and the nineteenth
annual genetic programming conference (GP-2014)",
- }
Genetic Programming entries for
Tomohiro Harada
Keiki Takadama
Citations