The Solution of Ordinary Differential Equations using Genetic Programming with Constant Tuning

Created by W.Langdon from gp-bibliography.bib Revision:1.8528

@InProceedings{Rockett:2025:UKCI,

• author = "Peter Rockett",
• title = "The Solution of Ordinary Differential Equations using Genetic Programming with Constant Tuning",
• booktitle = "24th UK Workshop on Computational Intelligence (UKCI 2025)",
• year = "2025",
• editor = "Emma Hart and Sarah L. Thomson and Zhiyuan Tan and Tomas Horvath and Neil Urquhart and Kehinde Babaagba",
• address = "Edinburgh Napier University",
• month = "3--5 " # sep,
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, ODE",
• URL = "https://eprints.whiterose.ac.uk/id/eprint/229165/",
• abstract = "we report the solution of a benchmark set of ordinary differential equations (ODEs) using genetic programming (GP) within a collocation framework using tuning of the embedded tree constants. We report statistical comparison with a baseline GP approach without constant tuning that indicates that parameter tuning produces statistically superior results. We obtain highly accurate solutions for almost all the benchmark ODEs, but identify a hitherto unreported issue with GP finding trivial solutions. The characteristics of the individual ODEs appear to dictate whether or not solution is problematic.",
• notes = "To be published after the conference",

}

Genetic Programming entries for Peter I Rockett

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