Graph Grammar Encoding and Evolution of Automata Networks
Created by W.Langdon from
gpbibliography.bib Revision:1.7686
 @InProceedings{Luerssen05,

author = "Martin H. Luerssen",

editor = "Vladimir EstivillCastro",

title = "Graph Grammar Encoding and Evolution of Automata
Networks",

booktitle = "TwentyEighth Australasian Computer Science Conference
(ACSC2005)",

series = "CRPIT",

volume = "38",

pages = "229238",

publisher = "ACS",

address = "Newcastle, Australia",

year = "2005",

month = jan # "/" # feb,

publisher = "Australian Computer Society, Inc.",

keywords = "genetic algorithms, genetic programming, graph
grammars, neural networks, ANN",

ISBN = "1920682201",

URL = "http://crpit.com/confpapers/CRPITV38Luerssen.pdf",

size = "4 pages",

abstract = "The global dynamics of automata networks (such as
neural networks) are a function of their topology and
the choice of automata used. Evolutionary methods can
be applied to the optimisation of these parameters, but
their computational cost is prohibitive unless they
operate on a compact representation. Graph grammars
provide such a representation by allowing network
regularities to be efficiently captured and reused. We
present a system for encoding and evolving automata
networks as collective hypergraph grammars, and
demonstrate its efficacy on the classical problems of
symbolic regression and the design of neural network
architectures.",

notes = "Also known as \cite{CRPITV38P229238}
\cite{DBLP:conf/acsc/Luerssen05}
ACSC '05",
 }
Genetic Programming entries for
Martin H Luerssen
Citations