Genetic Programming for the Automatic Inference of Graph Models for Complex Networks
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @Article{Bailey:2014:ieeeTEC,
-
author = "Alexander Bailey and Mario Ventresca and
Beatrice Ombuki-Berman",
-
title = "Genetic Programming for the Automatic Inference of
Graph Models for Complex Networks",
-
journal = "IEEE Transactions on Evolutionary Computation",
-
year = "2014",
-
volume = "18",
-
number = "3",
-
pages = "405--419",
-
month = jun,
-
keywords = "genetic algorithms, genetic programming, complex
networks, Evolutionary Computation",
-
ISSN = "1089-778X",
-
DOI = "doi:10.1109/TEVC.2013.2281452",
-
size = "15 pages",
-
abstract = "Complex networks are becoming an integral tool for our
understanding of an enormous variety of natural and
artificial systems. A number of human-designed network
generation procedures have been proposed that
reasonably model specific real-life phenomena in
structure and dynamics. Consequently, breakthroughs in
genetics, medicine, epidemiology, neuroscience,
telecommunications and the social sciences have
recently resulted. A graph model is an algorithm
capable of constructing arbitrarily sized networks,
whose end structure will exhibit certain statistical
and structural properties. The process of deriving an
accurate graph model is very time intensive and
challenging and may only yield highly accurate models
for very specific phenomena. An automated approach
based on Genetic Programming was recently proposed by
the authors. However, this initial system suffered from
a number of drawbacks, including an under-emphasis on
creating hub vertices, the requirement of user
intervention to determine objective weights and the
arbitrary approach to selecting the most representative
model from a population of candidate models. In this
paper we propose solutions to these problems and show
experimentally that the new system represents a
significant improvement and is very capable of
reproducing existing common graph models from even a
single small initial network.",
-
notes = "also known as \cite{6595618}",
- }
Genetic Programming entries for
Alexander Bailey
Mario Ventresca
Beatrice Ombuki-Berman
Citations