Application of advanced Grammatical Evolution to function prediction problem
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{Kuroda20101287,
-
author = "Takuya Kuroda and Hiroto Iwasawa and Eisuke Kita",
-
title = "Application of advanced Grammatical Evolution to
function prediction problem",
-
journal = "Advances in Engineering Software",
-
volume = "41",
-
number = "12",
-
pages = "1287--1294",
-
year = "2010",
-
ISSN = "0965-9978",
-
DOI = "doi:10.1016/j.advengsoft.2010.09.005",
-
URL = "http://www.sciencedirect.com/science/article/B6V1P-5167DR5-1/2/d992cacdff191a5bc78722add7146d07",
-
keywords = "genetic algorithms, genetic programming, Grammatical
Evolution, GE, Backus Naur Form, BNF, Function
prediction, Santa Fe trail, Nikkei stock average",
-
abstract = "Grammatical Evolution (GE) is one of the evolutionary
algorithms to find functions and programs, which can
deal according to a syntax with tree structure by
one-dimensional chromosome of Genetic Algorithm. An
original GE starts from the definition of the syntax by
means of Backus Naur Form (BNF). Chromosome in binary
number is translated to that in decimal number. The BNF
syntax selects according to the remainder of the
decimal number with respect to the total number of
candidate rules. In this study, we will introduce three
schemes for improving the convergence property of the
original GE. In numerical examples, the original GE is
compared in function identification problem with the
Genetic Programming (GP), which is one of the most
popular evolutionary algorithm to find unknown
functions or programs. Three algorithms are compared in
Santa Fe trail problem and prediction problem of Nikkei
stock average, which finds programs to control
artificial ants collecting foods. The results show that
the efficiency of schemes depends on the problem to be
solved and that the schemes 1 and 2 are effective for
Santa Fe trail problem and prediction problem of Nikkei
stock average, respectively.",
- }
Genetic Programming entries for
Takuya Kuroda
Hiroto Iwasawa
Eisuke Kita
Citations