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The problem with "evolutionary" circuits is that 99.99% of them don't work very well (dead organisms).

And that .01% often optimizes some weird corner case that kinda, sorta works but isn't really a "solution" (sickle cell anemia).

And in the .000001% case generates something genuinely useful (vision).

Gee, sort of like actual evolution, no?




That's my personal experience. With a single pass/fail condition most of the population tended to get trapped at the naieve solution - a 50% success rate.

This was the better part of a decade ago during my sophomore year of university, so it's entirely possible I somehow fucked up the backprop that was guiding it. In hindsight, maybe I was pruning too hard. But my experience was that it's hard to get your nets to develop the complexity to escape the basic naieve cases.




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