C. Ryan, и R. Azad. Genetic Programming, Proceedings of EuroGP'2003, том 2610 из LNCS, стр. 394--403. Essex, Springer-Verlag, (14-16 April 2003)
Аннотация
One of the key characteristics of Evolutionary
Algorithms is the manner in which solutions are evolved
from a primordial soup. The way this soup, or initial
generation, is created can have major implications for
the eventual quality of the search, as, if there is not
enough diversity, the population may become stuck on a
local optimum. This paper reports an initial
investigation using a position independent evolutionary
algorithm, Chorus, where the usual random
initialisation has been compared to an approach
modelled on the GP ramped half and half method. Three
standard benchmark problems have been chosen from the
GP literature for this study. It is shown that the new
initialisation method, termed sensible initialisation
maintains populations with higher average fitness
especially earlier on in evolution than with random
initialisation. Only one of the benchmarks fails to
show an improvement in a probability of success
measure, and we demonstrate that this is more likely a
symptom of issues with that benchmark than with the
idea of sensible initialisation. Performance seems to
be unaffected by the different derivation tree depths
used, and having a wider pool of individuals,
regardless of their average size, seems enough to
improve the performance of the system.
%0 Conference Paper
%1 ryan03a
%A Ryan, Conor
%A Azad, R. Muhammad Atif
%B Genetic Programming, Proceedings of EuroGP'2003
%C Essex
%D 2003
%E Ryan, Conor
%E Soule, Terence
%E Keijzer, Maarten
%E Tsang, Edward
%E Poli, Riccardo
%E Costa, Ernesto
%I Springer-Verlag
%K algorithms, evolution genetic grammatical programming,
%P 394--403
%T Sensible Initialisation in Chorus
%U http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2610&spage=394
%V 2610
%X One of the key characteristics of Evolutionary
Algorithms is the manner in which solutions are evolved
from a primordial soup. The way this soup, or initial
generation, is created can have major implications for
the eventual quality of the search, as, if there is not
enough diversity, the population may become stuck on a
local optimum. This paper reports an initial
investigation using a position independent evolutionary
algorithm, Chorus, where the usual random
initialisation has been compared to an approach
modelled on the GP ramped half and half method. Three
standard benchmark problems have been chosen from the
GP literature for this study. It is shown that the new
initialisation method, termed sensible initialisation
maintains populations with higher average fitness
especially earlier on in evolution than with random
initialisation. Only one of the benchmarks fails to
show an improvement in a probability of success
measure, and we demonstrate that this is more likely a
symptom of issues with that benchmark than with the
idea of sensible initialisation. Performance seems to
be unaffected by the different derivation tree depths
used, and having a wider pool of individuals,
regardless of their average size, seems enough to
improve the performance of the system.
%@ 3-540-00971-X
@inproceedings{ryan03a,
abstract = {One of the key characteristics of Evolutionary
Algorithms is the manner in which solutions are evolved
from a primordial soup. The way this soup, or initial
generation, is created can have major implications for
the eventual quality of the search, as, if there is not
enough diversity, the population may become stuck on a
local optimum. This paper reports an initial
investigation using a position independent evolutionary
algorithm, Chorus, where the usual random
initialisation has been compared to an approach
modelled on the GP ramped half and half method. Three
standard benchmark problems have been chosen from the
GP literature for this study. It is shown that the new
initialisation method, termed sensible initialisation
maintains populations with higher average fitness
especially earlier on in evolution than with random
initialisation. Only one of the benchmarks fails to
show an improvement in a probability of success
measure, and we demonstrate that this is more likely a
symptom of issues with that benchmark than with the
idea of sensible initialisation. Performance seems to
be unaffected by the different derivation tree depths
used, and having a wider pool of individuals,
regardless of their average size, seems enough to
improve the performance of the system.},
added-at = {2008-06-19T17:46:40.000+0200},
address = {Essex},
author = {Ryan, Conor and Azad, R. Muhammad Atif},
biburl = {https://www.bibsonomy.org/bibtex/2eb884bf3412a64ac9c0daf67987525ff/brazovayeye},
booktitle = {Genetic Programming, Proceedings of EuroGP'2003},
editor = {Ryan, Conor and Soule, Terence and Keijzer, Maarten and Tsang, Edward and Poli, Riccardo and Costa, Ernesto},
interhash = {8eceaec188c724f441ac0e0c62382a84},
intrahash = {eb884bf3412a64ac9c0daf67987525ff},
isbn = {3-540-00971-X},
keywords = {algorithms, evolution genetic grammatical programming,},
month = {14-16 April},
notes = {EuroGP'2003 held in conjunction with EvoWorkshops
2003},
organisation = {EvoNet},
pages = {394--403},
publisher = {Springer-Verlag},
publisher_address = {Berlin},
series = {LNCS},
timestamp = {2008-06-19T17:50:50.000+0200},
title = {Sensible Initialisation in Chorus},
url = {http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2610&spage=394},
volume = 2610,
year = 2003
}