Granted—it’s certainly an incredibly inefficient way of generating variation, but it’s infinitely better than no wiggling at all in that no wiggling would seem to deliver you unto the “stupid” algorithm which gets stuck at the local maxima.
In simulating biological evolution I might argue that random noise is a prerequisite to true congruence, but if the goal isn’t accurate emulation and instead is efficient optimization, more engineered noise seems to be the clear means to a trained algorithm.
This leads me to believe that, although ‘you cannot do exceptionally well by finding a noise source that is exceptionally random,’ there are specific use cases that make exceptional randomness desirable.
Re: Tim Tyler
Granted—it’s certainly an incredibly inefficient way of generating variation, but it’s infinitely better than no wiggling at all in that no wiggling would seem to deliver you unto the “stupid” algorithm which gets stuck at the local maxima.
In simulating biological evolution I might argue that random noise is a prerequisite to true congruence, but if the goal isn’t accurate emulation and instead is efficient optimization, more engineered noise seems to be the clear means to a trained algorithm.
This leads me to believe that, although ‘you cannot do exceptionally well by finding a noise source that is exceptionally random,’ there are specific use cases that make exceptional randomness desirable.