@Eli Tyre My guess would be that functions with more inputs/degrees of freedom have more and “harsher” optima/global optima with higher values than local optima. This can be tested by picking random functions on ℝⁿ, and testing different amounts of “optimization pressure” (ability to jump to maxima further away from the current local maximum) on sub-spaces of ℝⁿ. Is that what your confusion was about?
@Eli Tyre My guess would be that functions with more inputs/degrees of freedom have more and “harsher” optima/global optima with higher values than local optima. This can be tested by picking random functions on ℝⁿ, and testing different amounts of “optimization pressure” (ability to jump to maxima further away from the current local maximum) on sub-spaces of ℝⁿ. Is that what your confusion was about?