dc.contributor.author | Egri-Nagy, Attila | |
dc.contributor.author | Nehaniv, C.L. | |
dc.contributor.editor | Chalup, Stephan K. | |
dc.contributor.editor | Blair, Alan D. | |
dc.contributor.editor | Randall, Marcus | |
dc.date.accessioned | 2017-01-31T18:09:59Z | |
dc.date.available | 2017-01-31T18:09:59Z | |
dc.date.issued | 2015-01 | |
dc.identifier.citation | Egri-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.citation | conference | |
dc.identifier.isbn | 9783319148021 | |
dc.identifier.isbn | 978-3-319-14803-8 | |
dc.identifier.issn | 0302-9743 | |
dc.identifier.uri | http://hdl.handle.net/2299/17592 | |
dc.description | Attila 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.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. | en |
dc.format.extent | 14 | |
dc.format.extent | 328987 | |
dc.language.iso | eng | |
dc.publisher | Springer Nature | |
dc.relation.ispartof | Artificial Life and Computational Intelligence | |
dc.relation.ispartofseries | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | |
dc.subject | Cascade | |
dc.subject | Coordinatization | |
dc.subject | Decomposition | |
dc.subject | Permutation puzzle | |
dc.subject | Rubik’s cube | |
dc.subject | Wreath product | |
dc.subject | Computer Science(all) | |
dc.subject | Theoretical Computer Science | |
dc.title | Computational understanding and manipulation of symmetries | en |
dc.contributor.institution | Centre for Computer Science and Informatics Research | |
dc.contributor.institution | School of Computer Science | |
dc.contributor.institution | Science & Technology Research Institute | |
dc.contributor.institution | Adaptive Systems | |
rioxxterms.versionofrecord | 10.1007/978-3-319-14803-8_2 | |
rioxxterms.type | Other | |
herts.preservation.rarelyaccessed | true | |