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Gaussian Game of Life — discrete time
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Conway's Game of Life made continuous in space. The time remains discrete.
This version of the famous cellular automaton is inspired of Stephan Rafler's paper. The evolution rule is simplified (using linear functions instead of sigmoid ones) and the definition of the cell and the surrounding domains is improved (using a Gaussian distribution).
The colours are expressing the population density in the neighbourhood (which determines the evolution): blue if crowded, red if underpopulated.
Its numerical implementation (C++) is based on the convolution theorem, allowing us to use the Fast Fourier Transform algorithm.
The splitting rate of the gliders is adjustable changing the neighbourhood/cell sizes ratio.
This version of the famous cellular automaton is inspired of Stephan Rafler's paper. The evolution rule is simplified (using linear functions instead of sigmoid ones) and the definition of the cell and the surrounding domains is improved (using a Gaussian distribution).
The colours are expressing the population density in the neighbourhood (which determines the evolution): blue if crowded, red if underpopulated.
Its numerical implementation (C++) is based on the convolution theorem, allowing us to use the Fast Fourier Transform algorithm.
The splitting rate of the gliders is adjustable changing the neighbourhood/cell sizes ratio.