One other interesting discussion point in that book was that Cournot’s principle is inconcistent (or at least wrong), because in some situation any event which can happen has a very small probability. Glenn Shafer
proposes to fix this by replacing “practical certainty” with “prediction”. He may be right. After all, I mostly learned about Cournot’s principle from his
Why did Cournot’s principle disappear? and
“That’s what all the old guys said.” The many faces of Cournot’s principle. Another possible fix could be to evaluate smallness of probabilities relative to the entropy of the given situations. That solution came up during
discussions with kered rettop (Derek Potter?) on
robustness issues:
If an amplitude of 10^-1000 leads to totally different conclusions than an amplitude which is exactly zero, then the corresponding interpretation has robustness issues.
and was later used as an argument against
counting arguments in MWI:
For me, one reason to be suspicious of that counting of equally likely scenarios is that this runs into robustness issues again with very small probabilities like 10^-1000. You would have to construct a correspondingly huge amount of equally likely scenarios. But the very existence of such scenarios would imply an entropy much larger than physically reasonable. In fact, that entropy could be forced to be arbitrarily large.