Computational understanding and manipulation of symmetries

Attila Egri-Nagy, C.L. Nehaniv

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

For natural and artificial systems with some symmetry structure, computational understanding and manipulation can be achieved without learning by exploiting the algebraic structure. This algebraic coordinatization is based on a hierarchical (de)composition method. Here we describe this method and apply it to permutation puzzles. Coordinatization yields a structural understanding, not just solutions for the puzzles. In the case of the Rubik’s Cubes, different solving strategies correspond to different decompositions.

Original languageEnglish
Title of host publicationArtificial Life and Computational Intelligence
EditorsStephan K. Chalup, Alan D. Blair, Marcus Randall
PublisherSpringer Nature
Pages17-30
Number of pages14
Volume8955
ISBN (Electronic)978-3-319-14803-8
ISBN (Print)9783319148021
DOIs
Publication statusPublished - Jan 2015
Event1st Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2015 - Newcastle, United Kingdom
Duration: 5 Feb 20157 Feb 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8955
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2015
Country/TerritoryUnited Kingdom
CityNewcastle
Period5/02/157/02/15

Keywords

  • Cascade
  • Coordinatization
  • Decomposition
  • Permutation puzzle
  • Rubik’s cube
  • Wreath product

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