Derek P said:
I think it is a very awkward attempt to reinstate the idea of probability as a real property of the system. I don't know why anyone would want to do this as MWI seems to predict observation frequencies perfectly well without defining instrinsic probability or whatever you want to call it. But does it? This of course is why I started this thread
Without assuming the concept of probability, how would you define being successful at predicting observational frequencies?
If we use the concept of probability, there are familiar ways to define what it means to be successful at predicting observational frequencies - namely that the prediction method predicts a frequency that has a high probability of being the actual probability. However, what definition can we make without the concept of probability?
There have been attempts to found probability theory on actual frequencies, such as the "collectives" of Richard von Mises. However, I'm not aware of any that meet the modern standards of mathematical rigor.
There is the fundamental problem that "frequency" is a concept (initially) defined for finite numbers of events. For infinite collections of events, frequency must be defined as a limit. To define that limit, some way of considering only a finite number of events from the infinite collection must be specified.
Taking pains to speak only of frequencies, how do we decide if MWI predicts the Born Rule? It has to be something like "On the the most frequent branches ( i.e. the most frequent "wolds") , the frequency of events observed in a repeated experiment is approximately the frequency given by the Born Rule." The delicate part of that argument is how to define what finite sets of branches are used in computing the frequency of branches.
There is a non-circular and non-trivial aspect to the above argument. It is not self-evident that there is a single set of weights than can be used in defining how we pick finite sets of branches to use in defining their frequency that also works to produce the frequencies of events observed in experiments within the frequent branches. If such a set of weights exists, how do we know it is unique? If the weights exist and are unique, we still have to show they correspond to the numbers (for probabilities) given by the Born Rule.
The above type of argument using only frequencies can be disparaged as "branch counting". However, without taking the notion of probability as fundamental, I don't see any alternative approach.