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Overcoming Bias Commenter's avatar

Also I should have written U1 = a*z' instead of a*y.

Ah yes, right, of course.

Well, I grant that it is a reasonable sounding model. A pretty good one for a few days work, absolutely. Perhaps you should submit it to the Mathematical Contest in Modeling as a problem for them? Reading it reminded me of my years competing there. :)

I'm not convinced that it's necessarily much more accurate than some other plausible models, but it does have the advantage of much nicer looking mathematics than many alternatives, and that counts for a lot.

Anyone want to co-author something a write up of this? :)

Well, I am in Fairfax County and a probabilist... ;)

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Robin Hanson's avatar

You are both right; my error; I meant max posterior instead of max likelihood. Also I should have written U1 = a*z' instead of a*y. I've corrected these in the text above.

So, Eliezer, U = a*z(s') + Int_y p(y|s) log(p(y|s')) dy.

John, I took Eliezer's argument to be that there was a low probability effect that wasn't due to an attention payoff at all.

Yes, other models might give different results; this was the first one I tried. Yes, an obvious easy generalization is a general quadratic U1, which can express the diminishing returns Eliezer suggests.

Anyone want to co-author something a write up of this? :)

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