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Coscott comments on Bayesian probability as an approximate theory of uncertainty? - Less Wrong Discussion
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Comments (35)
I have also been having suspicions that I might have some issues with standard Bayesian probability. Specifically, I have been trying to see if I can do decision theory without defining probability theory, then define probabilities from decision theory. I will likely share my results in the near future.
Are you familiar with Leonard Savage's representation theorem? It sounds like what you're trying to do is pretty similar, so if you're unaware of Savage's work you might want to look into it, just to make sure you don't waste time retreading territory that has already been explored.
Also relevant: David Wallace's work on recovering the quantum mechanical Born probabilities from decision theory.
Thank you. I have not seen that theorem, and this is very helpful and interesting. It is incredibly similar to what I was doing. I strongly encourage anyone reading this to vote up pragmatist's comment.
I think most LWers working on these topics are already aware of Savage's approach. It doesn't work on AMD-like problems.
Are there any posts describing what goes wrong?
Piccione's paper, mentioned in Wei's post on AMD, says: