  Why are simple, regular, and symmetric shapes common in nature? Many natural
shapes arise as solutions to energy minimisation or other optimisation
problems, but is there a general relation between optima and simple, regular
shapes and geometries? Here we argue from algorithmic information theory that
for objective functions common in nature -- based on physics and engineering
laws -- optimal geometries will be simple, regular, and symmetric. Further, we
derive a null model prediction that if a given geometry is an optimal solution
for one natural objective function, then it is a priori more likely to be
optimal or close to optimal for another objective function.
