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