But for me it’s hard to see why “reality-fluid” (the name I give your “measure”, to remind myself that I don’t understand it at all) should dovetail so neatly with the information needed to locate events in universes or universes in Level IV.
Well, why would it be easier to locate some events or universes than others, unless they have more reality-fluid?
It’s clear why an epistemic prior is phrased this way—but why should reality-fluid behave likewise? Shades of either Mind Projection Fallacy or a very strange and very convenient coincidence.
Why is it possible to describe one mathematical structure more concisely than another, or to specify one computation using less bits than another? Is that just a property of the mind that’s thinking about these structures and computations, or is it actually a property of Reality? The latter seems more likely to me, given results in algorithmic information theory. (I don’t know if similar theorems has been or can be proven about set theory, that the shortest description lengths in different formalizations can’t be too far apart, but it seems plausible.)
Also, recall that in UDT, there is no epistemic prior. So, the only way to get an effect similar to EDT/CDT w/ universal prior, is with a weighting scheme over universes/events like I described.
I can sort of buy the part where simple universes have more reality-fluid, though frankly the whole setup strikes me as a mysterious answer to a mysterious question.
But the part where later events have less reality-fluid within a single universe, just because they take more info to locate—that part in particular seems really suspicious. MPF-ish.
Consider the case where you are trying to value (a) just yourself versus (b) the set of all future yous that satisfy the constraint of not going into negative utility.
The shannon information of the set (b) could be (probably would be) lower than that of (a). To see this, note that the complexity (information) of the set of all future yous is just the info required to specify (you,now) (because to compute the time evolution of the set, you just need the initial condition), whereas the complexity (information) of just you is a series of snapshots (you, now), (you, 1 microsecond from now), … . This is like the difference between a JPEG and an MPEG. The complexity of the constraint probably won’t make up for this.
If the constraint of going into negative utility is particularly complex, one could pick a simple subset of nonnegative utility future yous, for example by specifying relatively simple constraints that ensure that the vast majority of yous satisfying those constraints don’t go into negative utility.
This is problematic because it means that you would assign less value to a large set of happy future yous than to just one future you. A large and exhaustive set of future happy yous is less complex (easier to specify) than just one.
Well, why would it be easier to locate some events or universes than others, unless they have more reality-fluid?
Why is it possible to describe one mathematical structure more concisely than another, or to specify one computation using less bits than another? Is that just a property of the mind that’s thinking about these structures and computations, or is it actually a property of Reality? The latter seems more likely to me, given results in algorithmic information theory. (I don’t know if similar theorems has been or can be proven about set theory, that the shortest description lengths in different formalizations can’t be too far apart, but it seems plausible.)
Also, recall that in UDT, there is no epistemic prior. So, the only way to get an effect similar to EDT/CDT w/ universal prior, is with a weighting scheme over universes/events like I described.
I can sort of buy the part where simple universes have more reality-fluid, though frankly the whole setup strikes me as a mysterious answer to a mysterious question.
But the part where later events have less reality-fluid within a single universe, just because they take more info to locate—that part in particular seems really suspicious. MPF-ish.
I’m far from satisfied with the answer myself, but it’s the best I’ve got so far. :)
Consider the case where you are trying to value (a) just yourself versus (b) the set of all future yous that satisfy the constraint of not going into negative utility.
The shannon information of the set (b) could be (probably would be) lower than that of (a). To see this, note that the complexity (information) of the set of all future yous is just the info required to specify (you,now) (because to compute the time evolution of the set, you just need the initial condition), whereas the complexity (information) of just you is a series of snapshots (you, now), (you, 1 microsecond from now), … . This is like the difference between a JPEG and an MPEG. The complexity of the constraint probably won’t make up for this.
If the constraint of going into negative utility is particularly complex, one could pick a simple subset of nonnegative utility future yous, for example by specifying relatively simple constraints that ensure that the vast majority of yous satisfying those constraints don’t go into negative utility.
This is problematic because it means that you would assign less value to a large set of happy future yous than to just one future you. A large and exhaustive set of future happy yous is less complex (easier to specify) than just one.