General adversarial learning, where the noise is not purely random, but chosen to be the worst possible noise for you.
As renewed in fame recently by generative adversarial networks.
TBC: discuss politics implied by treating the learning as a battle with a conniving adversary as opposed to an uncaring universe, mention obvious connection with the theist neoreactionary zeitgeist. I’m sure someone has done this well in a terribly eloquent blog post, but I haven’t found one I’d want to link to yet.
Regardless of politically suggestive structure, application of game theory in the place of pure randomness and probably intersting / non-controversial in many areas although I don’t know most of them. Adverarial bandits is the obvious one in my world.
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