Fitness landscape analysis of dimensionally-aware genetic programming featuring feynman equations

M. Ðurasević, Domagoj Jakobovic, Marcella Scoczynski Ribeiro Martins, Stjepan Picek, Markus Wagner

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

Genetic programming is an often-used technique for symbolic regression: finding symbolic expressions that match data from an unknown function. To make the symbolic regression more efficient, one can also use dimensionally-aware genetic programming that constrains the physical units of the equation. Nevertheless, there is no formal analysis of how much dimensionality awareness helps in the regression process. In this paper, we conduct a fitness landscape analysis of dimensionally-aware genetic programming search spaces on a subset of equations from Richard Feynman’s well-known lectures. We define an initialisation procedure and an accompanying set of neighbourhood operators for conducting the local search within the physical unit constraints. Our experiments show that the added information about the variable dimensionality can efficiently guide the search algorithm. Still, further analysis of the differences between the dimensionally-aware and standard genetic programming landscapes is needed to help in the design of efficient evolutionary operators to be used in a dimensionally-aware regression.

Original languageEnglish
Title of host publicationParallel Problem Solving from Nature – PPSN XVI
EditorsThomas Bäck, Mike Preuss, André Deutz, Michael Emmerich, Hao Wang, Carola Doerr, Heike Trautmann
Place of PublicationCham
PublisherSpringer
Pages111-124
Number of pages14
EditionPart II
ISBN (Electronic)978-3-030-58115-2
ISBN (Print)978-3-030-58114-5
DOIs
Publication statusPublished - 2020
Event16th International Conference on Parallel Problem Solving from Nature, PPSN 2020 - Leiden, Netherlands
Duration: 5 Sep 20209 Sep 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer
Volume12270
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Parallel Problem Solving from Nature, PPSN 2020
CountryNetherlands
CityLeiden
Period5/09/209/09/20

Keywords

  • Dimensionally-Aware GP
  • Fitness landscape
  • Genetic programming
  • Local optima network

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