Can someone explain why UDT wasn’t good enough? In what case does UDT fail? (Or is it just hard to approximate with algorithms)?
I’ve been trying to understand the differences between TDT, UDT, and FDT, but they are not clearly laid out in any one place. The blog post that went along with the FDT paper sheds a little bit of light on it—it says that FDT is a generalization of UDT intended to capture the shared aspects of several different versions of UDT while leaving out the philosophical assumptions that typically go along with it.
That post also describes the key difference between TDT and UDT by saying that TDT “makes the mistake of conditioning on observations” which I think is a reference to Gary Drescher’s objection that in some cases TDT would make you decide as if you can choose the output of a pre-defined mathematical operation that is not part of your decision algorithm. I am still working on understanding Wei Dai’s UDT solution to that problem, but presumably FDT solves it in the same way.
I think it’s essentially UDT, rephrased to be more similar to classical CDT and EDT.