cygaril

Formalizations for the competition were done by hand.

Come up with many possible answers, formalize them all, and then try to prove or disprove each of them.

One possible cost measure is thr number of evaluations of the probability function.

I've done that many times and never used exact equality comparisons.

If you do exact comparisons for any non-trivial cases, you'll find different compilers, optimization settings, runtimes, and processors give different results.

Only if each value is equally likely. If you see $1,000 but figure the envelope-filler is a lot more likely to have been willing to put $1,500 in than $3,000 then you should stick.

You're assuming here that there are discrete stages that do different things. I think a better way to conceptualise these deepnets is that they're doing exactly what you want - each layer is "correcting" the mistakes of the previous layer.

Standard RL algorithms will converge to optimal play versus a fixed opponent, but will not find an optimal policy via self play.

One intuitive way to see this is that a sequence of improving pure policies A < B < C < etc. will converge to optimal play in a perfect information game like chess, but not necessarily in an imperfect information game like rock/paper/scissors where Rock < Paper < Scissors < Rock, etc

Seems to have missed the existence of jax.jit, which basically constructs an XLA program (call it a graph if you like) from your Python function which can then be optimized.

Or our entire evolutionary history of data.

I think you were right the first time.

Because you might think that people having employment is a good thing, worth encouraging through the tax / benefit system.

Also, tax credits can be (and are) paid weekly.

The proposed approach amounts to subsidizing human labour over automation. That night be a legitimate public policy aim.

I agree that rejection is always tough. I spent a year manoeuvring to be made redundant from a job I wanted to leave (e.g. told my boss I wanted to go, made sure everything I did was covered by other people). And still, when they did finally let me go, the rejection did hurt quite a bit.