2 Search Results for "Gacs, Peter"

Document
DOI: 10.4230/LIPIcs.STACS.2019.57
Random Noise Increases Kolmogorov Complexity and Hausdorff Dimension

Authors: Gleb Posobin and Alexander Shen

Published in: LIPIcs, Volume 126, 36th International Symposium on Theoretical Aspects of Computer Science (STACS 2019)

Abstract
Consider a bit string x of length n and Kolmogorov complexity alpha n (for some alpha<1). It is always possible to increase the complexity of x by changing a small fraction of bits in x [Harry Buhrman et al., 2005]. What happens with the complexity of x when we randomly change each bit independently with some probability tau? We prove that a linear increase in complexity happens with high probability, but this increase is smaller than in the case of arbitrary change considered in [Harry Buhrman et al., 2005]. The amount of the increase depends on x (strings of the same complexity could behave differently). We give exact lower and upper bounds for this increase (with o(n) precision). The same technique is used to prove the results about the (effective Hausdorff) dimension of infinite sequences. We show that random change increases the dimension with probability 1, and provide an optimal lower bound for the dimension of the changed sequence. We also improve a result from [Noam Greenberg et al., 2018] and show that for every sequence omega of dimension alpha there exists a strongly alpha-random sequence omega' such that the Besicovitch distance between omega and omega' is 0. The proofs use the combinatorial and probabilistic reformulations of complexity statements and the technique that goes back to Ahlswede, Gács and Körner [Ahlswede et al., 1976].
Cite as

Gleb Posobin and Alexander Shen. Random Noise Increases Kolmogorov Complexity and Hausdorff Dimension. In 36th International Symposium on Theoretical Aspects of Computer Science (STACS 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 126, pp. 57:1-57:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{posobin_et_al:LIPIcs.STACS.2019.57,
  author =	{Posobin, Gleb and Shen, Alexander},
  title =	{{Random Noise Increases Kolmogorov Complexity and Hausdorff Dimension}},
  booktitle =	{36th International Symposium on Theoretical Aspects of Computer Science (STACS 2019)},
  pages =	{57:1--57:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-100-9},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{126},
  editor =	{Niedermeier, Rolf and Paul, Christophe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2019.57},
  URN =		{urn:nbn:de:0030-drops-102969},
  doi =		{10.4230/LIPIcs.STACS.2019.57},
  annote =	{Keywords: Kolmogorov complexity, effective Hausdorff dimension, random noise}
}
Document
DOI: 10.4230/LIPIcs.STACS.2009.1828
Randomness on Computable Probability Spaces - A Dynamical Point of View

Authors: Peter Gacs, Mathieu Hoyrup, and Cristobal Rojas

Published in: LIPIcs, Volume 3, 26th International Symposium on Theoretical Aspects of Computer Science (2009)

Abstract
We extend the notion of randomness (in the version introduced by Schnorr) to computable Probability Spaces and compare it to a \emph{dynamical} notion of randomness: typicality. Roughly, a point is \emph{typical} for some dynamic, if it follows the statistical behavior of the system (Birkhoff's pointwise ergodic theorem). We prove that a point is Schnorr random if and only if it is typical for every \emph{mixing} computable dynamics. To prove the result we develop some tools for the theory of computable probability spaces (for example, morphisms) that are expected to have other applications.
Cite as

Peter Gacs, Mathieu Hoyrup, and Cristobal Rojas. Randomness on Computable Probability Spaces - A Dynamical Point of View. In 26th International Symposium on Theoretical Aspects of Computer Science. Leibniz International Proceedings in Informatics (LIPIcs), Volume 3, pp. 469-480, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{gacs_et_al:LIPIcs.STACS.2009.1828,
  author =	{Gacs, Peter and Hoyrup, Mathieu and Rojas, Cristobal},
  title =	{{Randomness on Computable Probability Spaces - A Dynamical Point of View}},
  booktitle =	{26th International Symposium on Theoretical Aspects of Computer Science},
  pages =	{469--480},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-09-5},
  ISSN =	{1868-8969},
  year =	{2009},
  volume =	{3},
  editor =	{Albers, Susanne and Marion, Jean-Yves},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2009.1828},
  URN =		{urn:nbn:de:0030-drops-18280},
  doi =		{10.4230/LIPIcs.STACS.2009.1828},
  annote =	{Keywords: Schnorr randomness, Birkhoff's ergodic theorem, Computable measures}
}
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