Standard tree-based genetic programming suffers from a
structural difficulty problem in that it is unable to
search effectively for solutions requiring very full or
very narrow trees. This deficiency has been variously
explained as a consequence of restrictions imposed by
the tree structure or as a result of the numerical
distribution of tree shapes. We show that by using a
different tree-based representation and local
(insertion and deletion) structural modification
operators, that this problem can be almost eliminated
even with trivial (stochastic hill-climbing) search
methods, thus eliminating the above explanations. We
argue, instead, that structural difficulty is a
consequence of the large step size of the operators in
standard genetic programming, which is itself a
consequence of the fixed-arity property embodied in its
representation.
%0 Journal Article
%1 HBE:IEETEC:06
%A Hoai, Nguyen Xuan
%A McKay, R. I. (Bob)
%A Essam, Daryl
%D 2006
%J IEEE Transactions on Evolutionary Computation
%K Deletion, algorithms, difficulty genetic insertion, operator, programming, representation, structural
%N 2
%P 157--166
%R doi:10.1109/TEVC.2006.871252
%T Representation and Structural Difficulty in Genetic
Programming
%U http://sc.snu.ac.kr/courses/2006/fall/pg/aai/GP/nguyen/Structdiff.pdf
%V 10
%X Standard tree-based genetic programming suffers from a
structural difficulty problem in that it is unable to
search effectively for solutions requiring very full or
very narrow trees. This deficiency has been variously
explained as a consequence of restrictions imposed by
the tree structure or as a result of the numerical
distribution of tree shapes. We show that by using a
different tree-based representation and local
(insertion and deletion) structural modification
operators, that this problem can be almost eliminated
even with trivial (stochastic hill-climbing) search
methods, thus eliminating the above explanations. We
argue, instead, that structural difficulty is a
consequence of the large step size of the operators in
standard genetic programming, which is itself a
consequence of the fixed-arity property embodied in its
representation.
@article{HBE:IEETEC:06,
abstract = {Standard tree-based genetic programming suffers from a
structural difficulty problem in that it is unable to
search effectively for solutions requiring very full or
very narrow trees. This deficiency has been variously
explained as a consequence of restrictions imposed by
the tree structure or as a result of the numerical
distribution of tree shapes. We show that by using a
different tree-based representation and local
(insertion and deletion) structural modification
operators, that this problem can be almost eliminated
even with trivial (stochastic hill-climbing) search
methods, thus eliminating the above explanations. We
argue, instead, that structural difficulty is a
consequence of the large step size of the operators in
standard genetic programming, which is itself a
consequence of the fixed-arity property embodied in its
representation.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Hoai, Nguyen Xuan and McKay, R. I. (Bob) and Essam, Daryl},
biburl = {https://www.bibsonomy.org/bibtex/266b510ee3e254d917f0bc0a0d5a9fafd/brazovayeye},
doi = {doi:10.1109/TEVC.2006.871252},
interhash = {b6d84131a8da04e5231b728eba37fb98},
intrahash = {66b510ee3e254d917f0bc0a0d5a9fafd},
journal = {IEEE Transactions on Evolutionary Computation},
keywords = {Deletion, algorithms, difficulty genetic insertion, operator, programming, representation, structural},
month = {April},
number = 2,
pages = {157--166},
size = {10 pages},
timestamp = {2008-06-19T17:41:35.000+0200},
title = {Representation and Structural Difficulty in Genetic
Programming},
url = {http://sc.snu.ac.kr/courses/2006/fall/pg/aai/GP/nguyen/Structdiff.pdf},
volume = 10,
year = 2006
}