Variants of Solomonoff induction

This page lists some variants of Solomonoff induction.

For determinism, I think "deterministic" is the same as "Solomonoff prior" and "stochastic" is the same as "universal mixture".

For discrete vs continuous, I think this just means whether the prior we define is over finite strings or over infinite sequences (where we want to know the probability of an infinite sequence starting with a given finite string).

Source	Formula	Determinism	Type of machine used	Discrete vs continuous
LessWrong Wiki	$m(y_{0})=\sum _{p\in {\mathcal {P}}:U(p)=y_{0}}2^{-\ell (p)}$ where ${\mathcal {P}}$ is the set of self-delimiting programs	Deterministic	Page doesn't say, but uses self-delimiting programs and it's discrete, so prefix Turing machine?	Discrete because the output string $y_{0}$ is finite
Scholarpedia discrete universal a priori probability	$m(x)=\sum _{p:U(p)=x}2^{-\ell (p)}$ where the sum is over halting programs	deterministic?	prefix Turing machine	discrete
Scholarpedia continuous universal a priori probability	$M(x)=\sum _{p:U(p)=x*}2^{-\ell (p)}$ where the sum is over minimal programs	deterministic?	Monotone Turing machine	Continuous
Sterkenburg (p. 22)	$P_{\mathrm {I} }(\sigma )=\lim _{n\to \infty }{\frac {|T_{\sigma ,n}|}{T_{n}}}$