A multi-level grammar approach to grammar-guided genetic programming: the case of scheduling in heterogeneous networks
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{Saber:GPEM,
-
author = "Takfarinas Saber and David Fagan and David Lynch and
Stepan Kucera and Holger Claussen and Michael O'Neill",
-
title = "A multi-level grammar approach to grammar-guided
genetic programming: the case of scheduling in
heterogeneous networks",
-
journal = "Genetic Programming and Evolvable Machines",
-
year = "2019",
-
volume = "20",
-
number = "2",
-
pages = "245--283",
-
month = jun,
-
keywords = "genetic algorithms, genetic programming,
Telecommunication, Heterogeneous network, Scheduling,
Grammar-guided genetic programming, Multi-level
grammar, Seeding",
-
ISSN = "1389-2576",
-
DOI = "doi:10.1007/s10710-019-09346-4",
-
size = "39 pages",
-
abstract = "The scale at which the human race consumes data has
increased exponentially in recent years. One key part
in this increase has been the usage of smart phones and
connected devices by the populous. Multi-level
heterogeneous networks are the driving force behind
this mobile revolution, but these are constrained with
limited bandwidth and over-subscription. Scheduling
users on these networks has become a growing issue. In
recent years grammar-guided genetic programming (G3P)
has shown its capability to evolve beyond
human-competitive network schedulers. Despite the
performance of the G3P schedulers, a large margin of
improvement is demonstrated to still exist. In the
pursuit of this goal we recently proposed a multi-level
grammar approach to generating schedulers. The
complexity of the grammar was increased at various
stages during evolution, allowing for individuals to
add more complex functions through variation
operations. The goal is to evolve good quality
solutions before allowing ...",
- }
Genetic Programming entries for
Takfarinas Saber
David Fagan
David Lynch
Stepan Kucera
Holger Claussen
Michael O'Neill
Citations