|
Hello, I’ve been using metavolv to tune parameters of
my program, and here is what I have to say. The program can’t deal with stochastic functions
at all. Even when the function shows a clear gradient at bigger scale, but is
noisy in small details, metavolv gets stuck in fictional local maxima created
by noise. I can provide some logs showing that. Mitchell writes in ‘discussion’
section of the manual about optimization of 4Play parameters: “In looking
at the parameter set, we see that most of the parameters changed very little,
indicating that our initial choices were not bad.” Well, I don’t
think so. It seems that parameters always change very little, because of the
noise problem. Description of what should be in ‘editThis.py’
file is insufficient; it takes time to guess what ‘resultPosition’ means, and I don’t
understand some others. Is it worth mentioning in manual that the program
requires 2 non-standard python packages: numpy and ctypes. Overall, the idea is nice, but it needs more
sophisticated search procedures. Why don’t you use a GA, for example? Kirill |
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