Abstract
This is a third paper in a series on shape decompositions, which are seen here as a means to grasp computations with shapes. That is, decompositions that arise in computations with shapes and may serve to explain them are investigated. Due to certain isomorphisms, computations with discrete and topological decompositions are carried out in parallel with shape computations thus providing insights into the latter. In particular, discrete decompositions grasp the transition of intuitive spatial computations envisioned by the designers into symbolic ones that could be carried out by a computer. Some counting has been done showing that even simple spatial computations require a great many symbols in order to be turned into the symbolic ones. It is interesting to explore the converse: turning complex symbolic computations with vast numbers of symbols into the simpler spatial ones with shapes. This may prove promising in tackling big data problems.
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Krstic, D. (2017). From Shape Computations to Shape Decompositions. In: Gero, J. (eds) Design Computing and Cognition '16. Springer, Cham. https://doi.org/10.1007/978-3-319-44989-0_14
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DOI: https://doi.org/10.1007/978-3-319-44989-0_14
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