Human Guidance Approaches for the Genetic Improvement of Software

Created by W.Langdon from gp-bibliography.bib Revision:1.7644

@InProceedings{Craine:2024:GI,

• author = "Benjamin J. Craine and Penn {Faulkner Rainford} and Barry Porter",
• title = "Human Guidance Approaches for the Genetic Improvement of Software",
• booktitle = "13th International Workshop on Genetic Improvement @ICSE 2024",
• year = "2024",
• editor = "Gabin An and Aymeric Blot and Vesna Nowack and Oliver Krauss and and and Justyna Petke",
• address = "Lisbon",
• month = "16 " # apr,
• publisher = "ACM",
• keywords = "genetic algorithms, genetic programming, Genetic Improvement, source code, fitness plateau, neutral search spaces, experienced human engineer",
• isbn13 = "979-8-4007-0573-1/24/04",
• URL = "http://gpbib.cs.ucl.ac.uk/gi2024/Craine_2024_GI.pdf",
• slides_url = "http://gpbib.cs.ucl.ac.uk/gi2024/gi_2024_slides/gi_icse2024_craine.pdf",
• size = "2 pages",
• abstract = "Existing research on Genetic Improvement (GI) of source code to improve performance \cite{rainford:2022:GECCO} has examined the mixed application of code synthesis and traditional GI mutation/crossover to gain higher-performing individuals that are tailored to particular deployment contexts, for examples such as hash tables or scheduling algorithms. While demonstrating successful improvements, this research presents a host of challenges \cite{Rainford:2021:GI}, from search space size to fitness landscape shape, which raise questions on whether GI alone is able to present a complete solution. In this position paper we propose to augment GI processes with Human Guidance (HG) to offer a co-pilot paradigm which may overcome these challenges.",
• notes = "GI @ ICSE 2024, part of \cite{an:2024:GI}",

}

Genetic Programming entries for Benjamin J Craine Penelope Faulkner Rainford Barry Porter

Citations