(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

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

License Rights

Restricted until