I want to believe that there is some optimal general prior, but it seems much more likely that we do not live in so convenient a world.
But if you can evaluate how good a prior is, then there has to be an optimal one (or several). You have to have something as your prior, and so whichever one is the best out of those you can choose is the one you should have. As for how certain you are that it's the best, it's (to some extent) turtles all the way down.
Instead of using "optimal general prior", I should have said that I was pessimistic about the existence of a standard for evaluating priors (or, more properly, prior probability distributions) that is optimal in all circumstances, if that's any clearer.
Having thought about the problem some more, though, I think my pessimism may have been premature.
A prior probability distribution is nothing more than a weighted set of hypotheses. A perfect Bayesian would consider every possible hypothesis, which is impossible unless hypotheses are countable, and ...
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