The “approachable technical details” I was imagining were of the form “What would an inference algorithm have to look like—how would it have to implicitly represent its probability distribution, and how inconsistent could that distribution be—in order for it to make sense to use it with UDT.” After having thought about it more, I realized these questions aren’t very extensive and basically boil down to the first example I gave.
Did you miss that part?
Yes. Moreover, I think I had never read your first post about UDT.
But it’s not clear that VNM axioms apply.
I don’t quite understand your objection, but probably because I am confused. What I imagine doing, very precisely, is this: using your preferences over outcomes and VNM, make a utility function, defined on outcomes. Using this utility function, offer wagers on mathematical statements (ie, offer bets of the form “You get outcome A; or, you get outcome B if statement X is true, and outcome C if statement X is false.”, where A, B, C have known utilities)
The “approachable technical details” I was imagining were of the form “What would an inference algorithm have to look like—how would it have to implicitly represent its probability distribution, and how inconsistent could that distribution be—in order for it to make sense to use it with UDT.” After having thought about it more, I realized these questions aren’t very extensive and basically boil down to the first example I gave.
Yes. Moreover, I think I had never read your first post about UDT.
I don’t quite understand your objection, but probably because I am confused. What I imagine doing, very precisely, is this: using your preferences over outcomes and VNM, make a utility function, defined on outcomes. Using this utility function, offer wagers on mathematical statements (ie, offer bets of the form “You get outcome A; or, you get outcome B if statement X is true, and outcome C if statement X is false.”, where A, B, C have known utilities)