Minor notation quibble to match our book: Usually one reserves as a generic Bayesian mixture:
and for a special case of with (the class of all lower semi-computable semimeasures) and , and for the Solomonoff Distribution
the sum over all programs fed to the universal monotone Turing machine that print something prefixed with , weighted by where is program length (write if choice of is clear from context). It is then proven that . Looks like you swap and ?
I think I didn’t swap them! The thing is that is an exact Bayesian mixture via the a priori prior that I use. I think my is the same thing as what you call the Solomonoff Distribution here.
Minor notation quibble to match our book: Usually one reserves
and
the sum over all programs
I think I didn’t swap them! The thing is that