- author = "Ting Hu and Gabriela Ochoa and Wolfgang Banzhaf",
- title = "Phenotype Search Trajectory Networks for Linear Genetic Programming",
- booktitle = "EuroGP 2023: Proceedings of the 26th European Conference on Genetic Programming",
- year = "2023",
- month = "12-14 " # apr,
- editor = "Gisele Pappa and Mario Giacobini and Zdenek Vasicek",
- series = "LNCS",
- volume = "13986",
- publisher = "Springer Verlag",
- address = "Brno, Czech Republic",
- pages = "52--67",
- organisation = "EvoStar, Species",
- keywords = "genetic algorithms, genetic programming, Neutral networks, Genotype-to-phenotype mapping, Algorithm modeling, Algorithm analysis, Search trajectories, Complex networks, Visualisation, Kolmogorov complexity",
- isbn13 = "978-3-031-29572-0",
-
URL = "
https://rdcu.be/c8UPb",
-
DOI = "
10.1007/978-3-031-29573-7_4",
- size = "16 pages",
- abstract = "we visualise the search trajectories of a genetic programming system as graph-based models, where nodes are genotypes/phenotypes and edges represent their mutational transitions. We also quantitatively measure the characteristics of phenotypes including their genotypic abundance (the requirement for neutrality) and Kolmogorov complexity. We connect these quantified metrics with search trajectory visualisations, and find that more complex phenotypes are under-represented by fewer genotypes and are harder for evolution to discover. Less complex phenotypes, on the other hand, are over-represented by genotypes, are easier to find, and frequently serve as stepping-stones for evolution.",
-
notes = "STN R code https://github.com/gabro8a/STNs
Part of \cite{Pappa:2023:GP} EuroGP'2023 held in conjunction with EvoCOP2023, EvoMusArt2023 and EvoApplications2023",
