  Algorithmic probability has shown some promise in dealing with the
probability problem in the Everett interpretation, since it provides an
objective, single-case probability measure. Many find the Everettian cosmology
to be overly extravagant, however, and algorithmic probability has also
provided improved models of subjective probability and Bayesian reasoning. I
attempt here to generalize algorithmic Everettianism to more Bayesian and
subjectivist interpretations. I present a general framework for applying
generative probability, of which algorithmic probability can be considered a
special case. I apply this framework to two commonly vexing thought experiments
that have immediate application to quantum probability: the Sleeping Beauty and
Replicator experiments.
