On Sun, Feb 23, 2020 at 11:36 PM Bruno Marchal <[email protected]> wrote:
> On 21 Feb 2020, at 11:41, Bruce Kellett <[email protected]> wrote: > > On Fri, Feb 21, 2020 at 9:30 PM Bruno Marchal <[email protected]> wrote: > >> >> But that argument would work for coin tossing too. That eliminate >> basically all probabilistic inference, it seems to me. A dwarf and a giant >> would not accept the Gaussian distribution of height. >> > > > You still don't get it, do you? The argument applies to all possible bit > strings of length N. You do not get that from coin tosses in a single > world. It is only when you claim that all possible results exist in > separate branching worlds that the problem arises. > > > I don’t see the relevance of the numbers of sequences with as much the > same W than M have any relevance with the inference of probabilities. It is > low, and the proportion is the same with or without the annihilation of the > copies, i.e. with self)duplication and coin tossing. I missed your point > indeed, but I don’t see the relevance. May be you elaborate. > In the coin tossing experiment, with N trials you get just a single binary string. With WM-dulicatin and N replications, you get all 2^N possible binary strings. I think this is a significant difference between the two cases. So it is a problem for your WM-duplication, and for Everett. > > > At least you see that connection (which John Clark seems to miss). > > > But not for single world theories. Statistical inference is perfectly > intact as it is used in this world. > > > I don’t see why this should not be the case in the WM self-dup, except > for a meagre, and negligible set of histories. It is the same in single > world: winning the big lottery three times in a row is rare. > That is where you make a fundamental mistake. The sequences with very unbalanced numbers of W and M are not rare in the WM-duplication case -- they always occur. The argument I have put forward shows that (always taking the first-person perspective) observers with these unbalanced sequences have every much right to use their data to infer a probability value as do those observers who get approximately equal numbers of Ws and Ms. There is no principled way from the 1p perspective in which you can distinguish these possibilities. So all sets of results are equally valid, as are all different probability estimates. Hence, there is no single preferred probability in the WM-duplication scenario. Bruce -- You received this message because you are subscribed to the Google Groups "Everything List" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/everything-list/CAFxXSLTbHie9F5bwteQFr1PxXH3nHGH4tuqr5QOmWBXrK8dKmw%40mail.gmail.com.
