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When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.STACS.2020.46
URN: urn:nbn:de:0030-drops-119071
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2020/11907/
Bauwens, Bruno
Information Distance Revisited
Abstract
We consider the notion of information distance between two objects x and y introduced by Bennett, Gács, Li, Vitanyi, and Zurek [C. H. Bennett et al., 1998] as the minimal length of a program that computes x from y as well as computing y from x, and study different versions of this notion. In the above paper, it was shown that the prefix version of information distance equals max (K(x|y),K(y|x)) up to additive logarithmic terms. It was claimed by Mahmud [Mahmud, 2009] that this equality holds up to additive O(1)-precision. We show that this claim is false, but does hold if the distance is at least logarithmic. This implies that the original definition provides a metric on strings that are at superlogarithmically separated.
BibTeX - Entry
@InProceedings{bauwens:LIPIcs:2020:11907,
author = {Bruno Bauwens},
title = {{Information Distance Revisited}},
booktitle = {37th International Symposium on Theoretical Aspects of Computer Science (STACS 2020)},
pages = {46:1--46:14},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-140-5},
ISSN = {1868-8969},
year = {2020},
volume = {154},
editor = {Christophe Paul and Markus Bl{\"a}ser},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2020/11907},
URN = {urn:nbn:de:0030-drops-119071},
doi = {10.4230/LIPIcs.STACS.2020.46},
annote = {Keywords: Kolmogorov complexity, algorithmic information distance}
}
Keywords: |
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Kolmogorov complexity, algorithmic information distance |
Collection: |
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37th International Symposium on Theoretical Aspects of Computer Science (STACS 2020) |
Issue Date: |
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2020 |
Date of publication: |
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04.03.2020 |