I certainly don’t say “it’s not hard work”, and the environmental probability distribution should not look like the probability distribution you have over your random numbers—it should contain correlations and structure. But once you know what your probability distribution is, then you should do your work relative to that, rather than assuming “worst case”. Optimizing for the worst case in environments that aren’t actually adversarial, makes even less sense than assuming the environment is as random and unstructured as thermal noise.
I would defend the following sort of statement: While often it’s not worth the computing power to take advantage of all the believed-in regularity of your probability distribution over the environment, any environment that you can’t get away with treating as effectively random, probably has enough structure to be worth exploiting instead of randomizing.
(This isn’t based on career experience, it’s how I would state my expectation given my prior theory.)
I certainly don’t say “it’s not hard work”, and the environmental probability distribution should not look like the probability distribution you have over your random numbers—it should contain correlations and structure. But once you know what your probability distribution is, then you should do your work relative to that, rather than assuming “worst case”. Optimizing for the worst case in environments that aren’t actually adversarial, makes even less sense than assuming the environment is as random and unstructured as thermal noise.
I would defend the following sort of statement: While often it’s not worth the computing power to take advantage of all the believed-in regularity of your probability distribution over the environment, any environment that you can’t get away with treating as effectively random, probably has enough structure to be worth exploiting instead of randomizing.
(This isn’t based on career experience, it’s how I would state my expectation given my prior theory.)