S. Shirakawa, S. Ogino, and T. Nagao. GECCO '07: Proceedings of the 9th annual conference on
Genetic and evolutionary computation, 2, page 1686--1693. London, ACM Press, (7-11 July 2007)
Abstract
In recent years a lot of Automatic Programming
techniques have developed. A typical example of
Automatic Programming is Genetic Programming (GP), and
various extensions and representations for GP have been
proposed so far. However, it seems that more
improvements are necessary to obtain complex programs
automatically. In this paper we proposed a new method
called Graph Structured Program Evolution (GRAPE). The
representation of GRAPE is graph structure, therefore
it can represent complex programs (e.g. branches and
loops) using its graph structure. Each program is
constructed as an arbitrary directed graph of nodes and
data set. The GRAPE program handles multiple data types
using the data set for each type, and the genotype of
GRAPE is the form of a linear string of integers. We
apply GRAPE to four test problems, factorial, Fibonacci
sequence, exponentiation and reversing a list, and
demonstrate that the optimum solution in each problem
is obtained by the GRAPE system.
GECCO '07: Proceedings of the 9th annual conference on
Genetic and evolutionary computation
year
2007
month
7-11 July
pages
1686--1693
publisher
ACM Press
volume
2
organisation
ACM SIGEVO (formerly ISGEC)
publisher_address
New York, NY, USA
size
8 pages
isbn13
978-1-59593-697-4
notes
GECCO-2007 A joint meeting of the sixteenth
international conference on genetic algorithms
(ICGA-2007) and the twelfth annual genetic programming
conference (GP-2007).
ACM Order Number 910071
Multiple data types. Graph may have several output
nodes. Genotype fixed length (linear!) vector of
integers. Genotype-phenotype.
%0 Conference Paper
%1 1277290
%A Shirakawa, Shinichi
%A Ogino, Shintaro
%A Nagao, Tomoharu
%B GECCO '07: Proceedings of the 9th annual conference on
Genetic and evolutionary computation
%C London
%D 2007
%E Thierens, Dirk
%E Beyer, Hans-Georg
%E Bongard, Josh
%E Branke, Jurgen
%E Clark, John Andrew
%E Cliff, Dave
%E Congdon, Clare Bates
%E Deb, Kalyanmoy
%E Doerr, Benjamin
%E Kovacs, Tim
%E Kumar, Sanjeev
%E Miller, Julian F.
%E Moore, Jason
%E Neumann, Frank
%E Pelikan, Martin
%E Poli, Riccardo
%E Sastry, Kumara
%E Stanley, Kenneth Owen
%E Stutzle, Thomas
%E Watson, Richard A
%E Wegener, Ingo
%I ACM Press
%K Fibonacci a algorithms, automatic based exponentiation, factorial, genetic graph list programming, reversing sequence,
%P 1686--1693
%T Graph structured program evolution
%U http://doi.acm.org/10.1145/1276958.1277290
%V 2
%X In recent years a lot of Automatic Programming
techniques have developed. A typical example of
Automatic Programming is Genetic Programming (GP), and
various extensions and representations for GP have been
proposed so far. However, it seems that more
improvements are necessary to obtain complex programs
automatically. In this paper we proposed a new method
called Graph Structured Program Evolution (GRAPE). The
representation of GRAPE is graph structure, therefore
it can represent complex programs (e.g. branches and
loops) using its graph structure. Each program is
constructed as an arbitrary directed graph of nodes and
data set. The GRAPE program handles multiple data types
using the data set for each type, and the genotype of
GRAPE is the form of a linear string of integers. We
apply GRAPE to four test problems, factorial, Fibonacci
sequence, exponentiation and reversing a list, and
demonstrate that the optimum solution in each problem
is obtained by the GRAPE system.
@inproceedings{1277290,
abstract = {In recent years a lot of Automatic Programming
techniques have developed. A typical example of
Automatic Programming is Genetic Programming (GP), and
various extensions and representations for GP have been
proposed so far. However, it seems that more
improvements are necessary to obtain complex programs
automatically. In this paper we proposed a new method
called Graph Structured Program Evolution (GRAPE). The
representation of GRAPE is graph structure, therefore
it can represent complex programs (e.g. branches and
loops) using its graph structure. Each program is
constructed as an arbitrary directed graph of nodes and
data set. The GRAPE program handles multiple data types
using the data set for each type, and the genotype of
GRAPE is the form of a linear string of integers. We
apply GRAPE to four test problems, factorial, Fibonacci
sequence, exponentiation and reversing a list, and
demonstrate that the optimum solution in each problem
is obtained by the GRAPE system.},
added-at = {2008-06-19T17:46:40.000+0200},
address = {London},
author = {Shirakawa, Shinichi and Ogino, Shintaro and Nagao, Tomoharu},
biburl = {https://www.bibsonomy.org/bibtex/2eb15428963876ba8c5842f2e22cce64d/brazovayeye},
booktitle = {GECCO '07: Proceedings of the 9th annual conference on
Genetic and evolutionary computation},
editor = {Thierens, Dirk and Beyer, Hans-Georg and Bongard, Josh and Branke, Jurgen and Clark, John Andrew and Cliff, Dave and Congdon, Clare Bates and Deb, Kalyanmoy and Doerr, Benjamin and Kovacs, Tim and Kumar, Sanjeev and Miller, Julian F. and Moore, Jason and Neumann, Frank and Pelikan, Martin and Poli, Riccardo and Sastry, Kumara and Stanley, Kenneth Owen and Stutzle, Thomas and Watson, Richard A and Wegener, Ingo},
interhash = {dec71fb69dcecef74242e6cc8c4f7c85},
intrahash = {eb15428963876ba8c5842f2e22cce64d},
isbn13 = {978-1-59593-697-4},
keywords = {Fibonacci a algorithms, automatic based exponentiation, factorial, genetic graph list programming, reversing sequence,},
month = {7-11 July},
notes = {GECCO-2007 A joint meeting of the sixteenth
international conference on genetic algorithms
(ICGA-2007) and the twelfth annual genetic programming
conference (GP-2007).
ACM Order Number 910071
Multiple data types. Graph may have several output
nodes. Genotype fixed length (linear!) vector of
integers. Genotype-phenotype.},
organisation = {ACM SIGEVO (formerly ISGEC)},
pages = {1686--1693},
publisher = {ACM Press},
publisher_address = {New York, NY, USA},
size = {8 pages},
timestamp = {2008-06-19T17:51:38.000+0200},
title = {Graph structured program evolution},
url = {http://doi.acm.org/10.1145/1276958.1277290},
volume = 2,
year = 2007
}