One of the major approaches in the field of
evolutionary computation is genetic programming.
Genetic programming tackles the issue of how to
automatically create a computer program for a given
problem from some initial problem statement. The goal
is accomplished by genetically breeding a population of
computer programs in terms of genetic operations. In
this paper, we describe a genetic programming system
called GAPS. GAPS has the following features: (1) It
implements the standard generational algorithm for
genetic programming with some refinement on controlling
introns growth during evolution process and improved
termination criteria. (2) It includes an extensible
language tailored to the needs of genetic programming.
And (3) It is a complete, standalone system that allows
for genetic programming tasks to be carried out without
requiring other tools such as compilers. Results with
GAPS have been satisfactory.
International Journal on Artificial Intelligence
Tools
номер
2
страницы
187--206
том
12
notes
An earlier version of this paper appears in the
Proceedings of IEEE COMPSAC 2000. This paper is a
substantially revised and extended version.
DBLP:conf/compsac/KramerZ00
%0 Journal Article
%1 DBLP:journals/ijait/ZhangK03
%A Zhang, Du
%A Kramer, Michael D.
%D 2003
%J International Journal on Artificial Intelligence
Tools
%K Evolutionary GP algorithms, computation, evaluation, fitness genetic introns operations, programming,
%N 2
%P 187--206
%R doi:10.1142/S0218213003001198
%T GAPS: A Genetic Programming System
%V 12
%X One of the major approaches in the field of
evolutionary computation is genetic programming.
Genetic programming tackles the issue of how to
automatically create a computer program for a given
problem from some initial problem statement. The goal
is accomplished by genetically breeding a population of
computer programs in terms of genetic operations. In
this paper, we describe a genetic programming system
called GAPS. GAPS has the following features: (1) It
implements the standard generational algorithm for
genetic programming with some refinement on controlling
introns growth during evolution process and improved
termination criteria. (2) It includes an extensible
language tailored to the needs of genetic programming.
And (3) It is a complete, standalone system that allows
for genetic programming tasks to be carried out without
requiring other tools such as compilers. Results with
GAPS have been satisfactory.
@article{DBLP:journals/ijait/ZhangK03,
abstract = {One of the major approaches in the field of
evolutionary computation is genetic programming.
Genetic programming tackles the issue of how to
automatically create a computer program for a given
problem from some initial problem statement. The goal
is accomplished by genetically breeding a population of
computer programs in terms of genetic operations. In
this paper, we describe a genetic programming system
called GAPS. GAPS has the following features: (1) It
implements the standard generational algorithm for
genetic programming with some refinement on controlling
introns growth during evolution process and improved
termination criteria. (2) It includes an extensible
language tailored to the needs of genetic programming.
And (3) It is a complete, standalone system that allows
for genetic programming tasks to be carried out without
requiring other tools such as compilers. Results with
GAPS have been satisfactory.},
added-at = {2008-06-19T17:46:40.000+0200},
author = {Zhang, Du and Kramer, Michael D.},
biburl = {https://www.bibsonomy.org/bibtex/2d09ab13086c3914aedaec46696d3aef6/brazovayeye},
doi = {doi:10.1142/S0218213003001198},
interhash = {eadb66670eae49733b6c38c1803f04dc},
intrahash = {d09ab13086c3914aedaec46696d3aef6},
journal = {International Journal on Artificial Intelligence
Tools},
keywords = {Evolutionary GP algorithms, computation, evaluation, fitness genetic introns operations, programming,},
month = {June 2003},
notes = {An earlier version of this paper appears in the
Proceedings of IEEE COMPSAC 2000. This paper is a
substantially revised and extended version.
\cite{DBLP:conf/compsac/KramerZ00}},
number = 2,
pages = {187--206},
timestamp = {2008-06-19T17:55:25.000+0200},
title = {{GAPS}: {A} Genetic Programming System},
volume = 12,
year = 2003
}