Two Problems for Sophistication

Peter Bloem, Steven de Rooij, Pieter Adriaans

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Kolmogorov complexity measures the amount of information in data, but does not distinguish structure from noise. Kolmogorov’s definition of the structure function was the first attempt to measure only the structural information in data, by measuring the complexity of the smallest model that allows for optimal compression of the data. Since then, many variations of this idea have been proposed, for which we use sophistication as an umbrella term. We describe two fundamental problems with existing proposals, showing many of them to be unsound. Consequently, we put forward the view that the problem is fundamental: it may be impossible to objectively quantify the sophistication.
Original languageEnglish
Title of host publicationAlgorithmic Learning Theory - 26th International Conference, ALT 2015
PublisherSpringer/Verlag
Pages379-394
Number of pages16
Volume9355
ISBN (Print)9783319244853
DOIs
Publication statusPublished - 2015
Externally publishedYes
Event26th International Conference on Algorithmic Learning Theory (ALT 2015) - Banff, Canada
Duration: 4 Oct 20156 Oct 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9355
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference26th International Conference on Algorithmic Learning Theory (ALT 2015)
CountryCanada
CityBanff
Period4/10/156/10/15

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