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by jacques_chester
2223 days ago
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There's a lot of literature spread across a bunch of fields. The one I first saw was "Active Nonlinear Tests"[0] from the systems dynamics / complex systems area. The idea is that you perform searches of parameter space for a simualation to find the places where it exhibits dramatic nonlinearities. I've since seen something similar but not identical in the Statistical Process Control world: robust process (or product) design[1]. The idea is that any given system can be thought of as a function that represents X = F(a, b, c, ...) + E, where E is some measure of error or noise that can't be removed. The goal is to find settings for a, b, c etc that minimise the effect of E. So that even if uncontrolled noise swirls around, your process remains stable. You can imagine flipping that to look for maxima instead. [0] https://www.santafe.edu/research/results/working-papers/acti... [1] Web search results are underwhelming, I refer you instead to Douglas Montgomery's Introduction to Statistical Process Control. |
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