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How do you
optimise in a very high-
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dimensional
space?
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Hard
to calculate derivatives due to stochastic
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noise
and sheer number of dimensions
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Can
use a genetic algorithm
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Begins
with random designs
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Improves
with mutation, interpolation, crossover…
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Has
been highly successful so far in problems
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with
up to 137 parameters
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