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(2015) Artificial life and computational intelligence, Dordrecht, Springer.
Computational understanding and manipulation of symmetries
Attila Egri-Nagy , Chrystopher L. Nehaniv
pp. 17-30
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.
Publication details
DOI: 10.1007/978-3-319-14803-8_2
Full citation:
Egri-Nagy, A. , Nehaniv, C. L. (2015)., Computational understanding and manipulation of symmetries, in M. Randall (ed.), Artificial life and computational intelligence, Dordrecht, Springer, pp. 17-30.