And as long as P(U($10)>U($5)) is large enough a priori, it will swamp out the difference.
Well, then why even update? (Or, more specifically, why assume that this is harmless normally, but an ace up your sleeve for a particular class of problems? You need to be able to reliably distinguish when this helps you and when this hurts you from the inside, which seems difficult.)
Because I can’t prove that I’ll go through this line of reasoning. Simulating my decision process as part of my decision would result in infinite recursion.
I’m not sure that I understand this; I’m under the impression that many TDT applications require that they be able to simulate themselves (and other TDT reasoners) this way.
Good questions. I don’t know the answers. But like you say, UDT especially is basically defined circularly—where the agent’s decision is a function of itself. Making this coherent is still an unsolved problem. So I was wondering if we could get around some of the paradoxes by giving up on certainty.
Well, then why even update? (Or, more specifically, why assume that this is harmless normally, but an ace up your sleeve for a particular class of problems? You need to be able to reliably distinguish when this helps you and when this hurts you from the inside, which seems difficult.)
I’m not sure that I understand this; I’m under the impression that many TDT applications require that they be able to simulate themselves (and other TDT reasoners) this way.
Good questions. I don’t know the answers. But like you say, UDT especially is basically defined circularly—where the agent’s decision is a function of itself. Making this coherent is still an unsolved problem. So I was wondering if we could get around some of the paradoxes by giving up on certainty.