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This paper explores temporal and spatial dynamics of a population of Genetic Regulatory Networks (GRN). In order to so, a GRN model is spatially distributed to solve a multi-cellular Artificial Embryogeny problem, and Evolutionary Computation is used to optimize the developmental sequences. An in-depth analysis is provided and shows that such a population of GRN displays strong spatial synchronization as well as various kinds of behavioral patterns, ranging from smooth diffusion to abrupt transition patterns.
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