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Morendil comments on What is Wei Dai's Updateless Decision Theory? - Less Wrong
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Thanks - it's helpful even to have negative feedback like this, to get a better idea of where to 'pitch' any future posts I make.
For what it's worth, my post presupposes basic knowledge of probability theory, conditional probabilities and Bayesian reasoning, and enough familiarity with and understanding of the problems mentioned to more or less 'instantly see' how they are related to my diagrammatic depictions.
I guess that won't be very helpful, but I'd be happy to answer any specific questions you may have.
As regards probability it may be useful to think of me as a possibly confused student. This is stuff I'm learning, and there are bound to be gaps in my knowledge.
What do you mean by "unconditional expected utility"?
I understand expectation (probability weighted sum of possible values), I understand utility (measure of satisfaction of an agent's preferences), and I understand conditioning as a basic operation in probability.
In particular, how does your distinction between NDT and UDT play out in numbers in (say) the Sleeping Beauty scenario? How exactly is NDT inadequate there?
The Sleeping Beauty scenario is problematic to discuss because it's posed as a question about probabilities rather than utilities. Let's consider Parfit's Hitchhiker instead. If you'd like some concrete numbers, suppose you get 0 utility if you're left in the desert, 10 if you're taken back to civilisation, but then lose 1 if you have to pay. So the utilities in the 'Util' boxes on my diagram are 9, 10, 0, in that order.
Now, if you have an opportunity to act at all, then you can say with certainty where you are in the tree-diagram: you're at the one-and-only Player node. This corresponds to "I've already been taken to my destination, and now I need to decide whether to pay the driver." Conditional upon being at that node, it's obvious that you maximise your utility by not paying (10 instead of 9).
However, if you make no assumptions about 'the state of the world' (i.e. whether or not you were offered a ride) and ask "Which of the two strategies maximizes my expected utility at the outset?" then the strategy where you pay up will get utility 9, and the one that doesn't will get 0.
So looking at the unconditional expected utility basically means that you deliberately 'forget' the information you have about where you are in the game and just look for "a strategy for the blue box" that will maximize your utility over many start-to-finish iterations of the game.
I don't know where the probabilities are supposed to be in that graphical model, so I don't know how to apply my understanding of "expectation". I'm not even sure what I'm supposed to be uncertain about, so I'm not sure how to apply my understanding of "probability".
I don't know what the semantics of nodes and arrows are, either. Labeling the arrows and the "Util" boxes would help.
That might justify removing it from the OP, or at least moving it out of the critical path across the inferential distance.
It isn't clear how you can discuss expectations without discussing probabilities?
In the case of Newcomb's Problem - if Omega is only assumed to have some finite accuracy, say .9 - I can at least start to see how to make it about probabilities and expectations. I'll take a shot at it sometime.