- author = "William B. Langdon and David Clark",
- title = "Population Diversity, Information Theory and Genetic Improvement",
- booktitle = "European Conference on Genetic Programming, EuroGP 2025",
- year = "2025",
- editor = "Bing Xue and Luca Manzoni and Illya Bakurov",
- address = "Trieste",
- month = "23-25 " # apr,
- note = "Forthcoming",
- keywords = "genetic algorithms, genetic programming, Genetic Improvement, Evolutionary computing, EC, GP, SBSE, Software Engineering, Information theory, Normalised Compression Distance, NCD, Normalised Information Distance, NID, perf, test set diameter, selection",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/Langdon_2025_EuroGP.pdf",
- size = "19 pages",
- abstract = "Compression, e.g. gzip, gives algorithmic information theory (Kolmogorov Complexity) based measures of string population diversity. To boost it we use the GI tool Magpie and select programs of average fitness that contribute most to variety, allowing evolution to automatically tailor triangle.c for production speed. We calculate C source code diversity via approximations to the Normalised Compression Distance on Multisets (NCDm) using both Cohen and Vitanyi's O(n squared) approach and our own, O(n) method, finding the cheaper, O(n), is equally good.",
-
notes = "also known as \cite{paper_49_genetic_improvement}
Part of \cite{Xue:2025:GP} EuroGP'2025 held in conjunction with EvoCOP2025, EvoMusArt2025 and EvoApplications2025",
