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dc.contributor.authorEgri-Nagy, Attila
dc.contributor.authorNehaniv, C.L.
dc.contributor.editorChalup, Stephan K.
dc.contributor.editorBlair, Alan D.
dc.contributor.editorRandall, Marcus
dc.date.accessioned2017-01-31T18:09:59Z
dc.date.available2017-01-31T18:09:59Z
dc.date.issued2015-01
dc.identifier.citationEgri-Nagy , A & Nehaniv , C L 2015 , Computational understanding and manipulation of symmetries . in S K Chalup , A D Blair & M Randall (eds) , Artificial Life and Computational Intelligence . vol. 8955 , Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , vol. 8955 , Springer Nature , pp. 17-30 , 1st Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2015 , Newcastle , United Kingdom , 5/02/15 . https://doi.org/10.1007/978-3-319-14803-8_2
dc.identifier.citationconference
dc.identifier.isbn9783319148021
dc.identifier.isbn978-3-319-14803-8
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/2299/17592
dc.descriptionAttila Egri-Nagy, Chrystopher L Nehaniv, "Computational Understanding and Manipulation of Symmetries", in Chalup S. K., Blair A. D., Randall M. (Eds) Artificial Life and Computational Intelligence ACALCI, First Australasian Conference, Newcastle, NSW, Australia, February 5-7 2015, Proceedings, Lecture Notes in Computer Science, Vol. 8955, 2015 © Springer International Publishing Switzerland 2015 Final, published version of this paper is available online via doi: 10.1007/978-3-319-14803-8_2
dc.description.abstractFor 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.en
dc.format.extent14
dc.format.extent328987
dc.language.isoeng
dc.publisherSpringer Nature
dc.relation.ispartofArtificial Life and Computational Intelligence
dc.relation.ispartofseriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.subjectCascade
dc.subjectCoordinatization
dc.subjectDecomposition
dc.subjectPermutation puzzle
dc.subjectRubik’s cube
dc.subjectWreath product
dc.subjectComputer Science(all)
dc.subjectTheoretical Computer Science
dc.titleComputational understanding and manipulation of symmetriesen
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionScience & Technology Research Institute
dc.contributor.institutionAdaptive Systems
rioxxterms.versionofrecord10.1007/978-3-319-14803-8_2
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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