A Theoretical Study On Fitness Supremum in Linear Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8834
- @InCollection{Huang:2026:raLGP,
-
author = "Zhixing Huang and Yi Mei and Fangfang Zhang and
Mengjie Zhang and Wolfgang Banzhaf",
-
title = "A Theoretical Study On Fitness Supremum in Linear
Genetic Programming",
-
booktitle = "Recent Advances in Linear Genetic Programming",
-
publisher = "Springer",
-
year = "2026",
-
editor = "Wolfgang Banzhaf and Ting Hu",
-
chapter = "3",
-
pages = "23--52",
-
note = "forthcoming",
-
keywords = "genetic algorithms, genetic programming, Linear
Genetic Programming, Introns and Exons, Freemut",
-
abstract = "we take linear genetic programming (LGP) as an example
to theoretically study the relationship between
genotype and fitness. We find that the fitness
expectation value increases with fitness supremum
(i.e., the worst possible fitness value) over
instruction editing distance (i.e., the number of
changing instructions from one program to another). We
then extend these findings to explain the bloat effect
and the first hitting time of LGP. The reported
empirical results verify our hypothesis. we extend the
key insights from the theoretical analysis and discuss
the future directions.",
-
notes = "part of \cite{Banzhaf:2026:raLGP_book}",
- }
Genetic Programming entries for
Zhixing Huang
Yi Mei
Fangfang Zhang
Mengjie Zhang
Wolfgang Banzhaf
Citations