Created by W.Langdon from gp-bibliography.bib Revision:1.2031
@InProceedings{lucas:2002:esmatfges,
author = "Simon Lucas",
title = "Evolving spring-mass models: a test-bed for graph
encoding schemes",
booktitle = "Proceedings of the 2002 Congress on Evolutionary
Computation CEC2002",
editor = "David B. Fogel and Mohamed A. El-Sharkawi and
Xin Yao and Garry Greenwood and Hitoshi Iba and Paul Marrow and
Mark Shackleton",
pages = "1952--1957",
year = "2002",
publisher = "IEEE Press",
publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
08855-1331, USA",
organisation = "IEEE Neural Network Council (NNC), Institution of
Electrical Engineers (IEE), Evolutionary Programming
Society (EPS)",
ISBN = "0-7803-7278-6",
month = "12-17 " # may,
notes = "CEC 2002 - A joint meeting of the IEEE, the
Evolutionary Programming Society, and the IEE. Held in
connection with the World Congress on Computational
Intelligence (WCCI 2002)",
URL = "
http://algoval.essex.ac.uk/rep/springs/cec2002.pdf",
keywords = "genetic algorithms, genetic programming",
abstract = "For many interesting design problems the solution is
most naturally represented as a type of graph. This
paper proposes that the problem of evolving spring-mass
models for a set of design challenges makes an
excellent test-bed for evaluating the performance of
various graph encoding schemes. We describe how the
problem is set up, and intro-duce a planar graph coding
scheme. Results demonstrate that the planar graph
encoding scheme significantly out-performs a simple
direct encoding scheme on a height-challenge design
problem.",
}
Genetic Programming entries for Simon M Lucas