Earlier quoted context omitted.
I didn't claim it did - all I said is that this gives Occams Razor as an asymptotic law. Intuitively, I'm claiming: Lim_{complexity -> infinity} P(theory having fixed complexity) = 0 Stated more precisely, fix a prior distribution, then for any epsilon > 0, I can find a complexity cutoff C (which depends on the prior) so that P(any theory with complexity > C being true) This doesn't mean that P(theory|complexity) is…
Here's an argument that runs completely parallel: jwmerrill's razor: points in the plane should be considered to be close to the origin unless there is evidence otherwise. Is this a reasonable law? As reasonable as Occam's razor? I think probably not, but I don't have a strong opinion. One interesting thing to note is that the law doesn't say where the origin is (similarly, Occam's razor is vague about what exactly i…
I don't really know why you don't think that the asymptotic forms are evidence in favor of this - a prototypical probability distribution on the real line is a bump somewhere with a decaying tail. And that "somewhere" is far closer to the origin than points out in some arbitrarily distant tail.
Now obviously if you want to make stronger claims about a specific origin, you'll need to specify a particular probability distribution, and justify why that's the right one. I agree that a non-asymptotic Occams razor is an additional assumption.
But you also get pretty far with the asymptotic theory. Consider a theory of "green" as compared to a theory of "bleen" (namely that green turns to blue after some time T). You have a prior with some probability that only green exists (say 50%), and also a 50% chance that green turns to blue after some time T. But now you have a continuous distribution over T.
Now suppose you want to make a prediction - e.g., H = "the grass will be green, not blue, at t=50". When you compute a posterior, you reject all values of T 50 actually yield the same prediction as "only green exists". So the only way you can get a prediction of blue at time 50 is if 0 I do in fact hold the view that Bayesian probability is a consistent theory of the scientific method, and also of how humans should update their beliefs when new evidence is gathered.
(Minor nit: your continuous asymptotic form isn't slightly wrong for this purpose, f(x) need not approach zero. Counterexample: f(x) = 1 for x \in [1, 1+2^{-1}], [2, 2+2^{-2}], etc, f(x) = 0 elsewhere. That integrates out to 1/2 + 1/4 + ... = 1, but lim_{x -> \infty} f(x) doesn't exist.)
[I'm also a bit surprised you are being so heavily downvoted. I don't think you are right, but you are hardly so crazily wrong that you should be greyed out.]