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Differentiable cellular automata

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arxiv 1708.09546 v1 pith:JTQM7IWI submitted 2017-08-31 cs.DM nlin.CG

classification cs.DMnlin.CG
keywords automatacellulardcasdifferentiableordinarybehaviorclasscomputed
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We describe a class of cellular automata (CAs) that are end-to-end differentiable. DCAs interpolate the behavior of ordinary CAs through rules that act on distributions of states. The gradient of a DCA with respect to its parameters can be computed with an iterative propagation scheme that uses previously-computed gradients and values. Gradient-based optimization over DCAs could be used to find ordinary CAs with desired properties.

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Cited by 1 Pith paper

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  1. Differentiable Logic Cellular Automata: From Game of Life to Pattern Generation

    cs.AI 2025-06 conditional novelty 6.0 of 10

    A recurrent circuit of differentiable logic gates learns local update rules for cellular automata, reproducing Game of Life and generating target patterns.

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