Computational understanding and manipulation of symmetries

Egri-Nagy, Attila and Nehaniv, C.L. (2015) Computational understanding and manipulation of symmetries. In: Artificial Life and Computational Intelligence :. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8955 . Springer Nature, GBR, pp. 17-30. ISBN 9783319148021
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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.


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