We introduce a generative system for "avoidance drawings", drawings made by virtual drawing robots executing a random walk while simultaneously avoiding the paths of other robots. The random walk method is unique and is based on a curvature controlling scheme initially introduced by Chappell. We design a fitness function for evaluating avoidance drawings and an evolutionary framework for evolving them. This requires us to follow principles we elucidate for simulated evolution where the generative system is highly stochastic in nature. Examples document the evolutionary system's efficacy and success.
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