(Non-)Equivalence of universal priors
Date
2011-11
Authors
Wood, Ian
Sunehag, Peter
Hutter, Marcus
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Verlag
Abstract
Ray Solomonoff invented the notion of universal induction featuring an aptly termed “universal” prior probability function over all possible computable environments [9]. The essential property of this prior was its ability to dominate all other such priors. Later, Levin introduced another construction — a mixture of all possible priors or “universal mixture”[12]. These priors are well known to be equivalent up to multiplicative constants. Here, we seek to clarify further the relationships between these three characterisations of a universal prior (Solomonoff’s, universal mixtures, and universally dominant priors). We see that the the constructions of Solomonoff and Levin define an identical class of priors, while the class of universally dominant priors is strictly larger. We provide some characterisation of the discrepancy.
Description
Keywords
algorithmic information theory, universal induction, universal prior
Citation
Collections
Source
Type
Conference paper
Book Title
Algorithmic probability and friends : Bayesian prediction and artificial intelligence, papers from the Ray Solomonoff 85th memorial conference, Melbourne, Vic, Australia, November 30 - December 2, 2011
Entity type
Access Statement
Open Access