Hash-Based Tree Similarity and Simplification in Genetic Programming for Symbolic Regression

التفاصيل البيبلوغرافية
العنوان: Hash-Based Tree Similarity and Simplification in Genetic Programming for Symbolic Regression
المؤلفون: Lukas Kammerer, Michael Affenzeller, Bogdan Burlacu, Gabriel Kronberger
المصدر: Computer Aided Systems Theory – EUROCAST 2019 ISBN: 9783030450922
EUROCAST (1)
بيانات النشر: Springer International Publishing, 2020.
سنة النشر: 2020
مصطلحات موضوعية: Theoretical computer science, Computer science, Hash function, Genetic programming, 02 engineering and technology, Tree (data structure), Similarity (network science), Simple (abstract algebra), 020204 information systems, ComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION, 0202 electrical engineering, electronic engineering, information engineering, Benchmark (computing), 020201 artificial intelligence & image processing, Binary expression tree, Symbolic regression
الوصف: We introduce in this paper a runtime-efficient tree hashing algorithm for the identification of isomorphic subtrees, with two important applications in genetic programming for symbolic regression: fast, online calculation of population diversity and algebraic simplification of symbolic expression trees. Based on this hashing approach, we propose a simple diversity-preservation mechanism with promising results on a collection of symbolic regression benchmark problems.
ردمك: 978-3-030-45092-2
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::9c602bb4f880d6065a9138400c4c196c
https://doi.org/10.1007/978-3-030-45093-9_44
حقوق: OPEN
رقم الأكسشن: edsair.doi...........9c602bb4f880d6065a9138400c4c196c
قاعدة البيانات: OpenAIRE