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by Vanessa Kosoy 1179 days ago | Abram Demski likes this | link | parent

I think that the idea that contradictions should lead to infinite utility is probably something that doesn’t work for real models of logical uncertainty. Instead we can do pseudorandomization. That said, there might be some other approach that I’m missing.

Maximizing \(E[U \mid A() = a]\) is not EDT. In fact I believe it is the original formulation of UDT. The problems with EDT arise when you condition by indexical uncertainty. Instead, you should condition by logical uncertainty while fixing indexical uncertainty (see also this). I think that the correct decision theory has to look like evaluating some sort of expected values since the spirit of VNM theory should survive.

I think that the idea of gradually increasing the power of utility estimation corresponds precisely to going to higher metathreat levels, since the implementation of metathreats by optimal predictors involves pseudorandomizing each level while using more powerful predictors on the next level that are able to simulate the pseudorandom. This should also solve logical counterfactual mugging where the logical coin looks random on the lower levels allowing pre-committing to cooperative behavior on the higher levels on which the logical coin looks deterministic.



by Alex Mennen 1179 days ago | link

I think that the idea that contradictions should lead to infinite utility is probably something that doesn’t work for real models of logical uncertainty.

Why not?

In fact I believe it is the original formulation of UDT.

Huh, you’re right. I even knew that at one point. Specifically, what I proposed was UDT 1 (in this write-up’s terminology), and I concluded that what I described was not UDT because I found a bug in it that I thought UDT should get right (and which UDT 1.1 does get right).

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