5 Search Results for "H�lzl, Rupert"

Document
DOI: 10.4230/LIPIcs.STACS.2017.17
Monte Carlo Computability

Authors: Vasco Brattka, Rupert Hölzl, and Rutger Kuyper

Published in: LIPIcs, Volume 66, 34th Symposium on Theoretical Aspects of Computer Science (STACS 2017)

Abstract
We introduce Monte Carlo computability as a probabilistic concept of computability on infinite objects and prove that Monte Carlo computable functions are closed under composition. We then mutually separate the following classes of functions from each other: the class of multi-valued functions that are non-deterministically computable, that of Las Vegas computable functions, and that of Monte Carlo computable functions. We give natural examples of computational problems witnessing these separations. As a specific problem which is Monte Carlo computable but neither Las Vegas computable nor non-deterministically computable, we study the problem of sorting infinite sequences that was recently introduced by Neumann and Pauly. Their results allow us to draw conclusions about the relation between algebraic models and Monte Carlo computability.
Cite as

Vasco Brattka, Rupert Hölzl, and Rutger Kuyper. Monte Carlo Computability. In 34th Symposium on Theoretical Aspects of Computer Science (STACS 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 66, pp. 17:1-17:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{brattka_et_al:LIPIcs.STACS.2017.17,
  author =	{Brattka, Vasco and H\"{o}lzl, Rupert and Kuyper, Rutger},
  title =	{{Monte Carlo Computability}},
  booktitle =	{34th Symposium on Theoretical Aspects of Computer Science (STACS 2017)},
  pages =	{17:1--17:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-028-6},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{66},
  editor =	{Vollmer, Heribert and Vall\'{e}e, Brigitte},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2017.17},
  URN =		{urn:nbn:de:0030-drops-70164},
  doi =		{10.4230/LIPIcs.STACS.2017.17},
  annote =	{Keywords: Weihrauch degrees, Weak Weak Konig's Lemma, Monte Carlo computability, algorithmic randomness, sorting}
}
Document
DOI: 10.4230/LIPIcs.STACS.2015.130
Las Vegas Computability and Algorithmic Randomness

Authors: Vasco Brattka, Guido Gherardi, and Rupert Hölzl

Published in: LIPIcs, Volume 30, 32nd International Symposium on Theoretical Aspects of Computer Science (STACS 2015)

Abstract
In this article we try to formalize the question "What can be computed with access to randomness?" We propose the very fine-grained Weihrauch lattice as an approach to differentiate between different types of computation with access to randomness. In particular, we show that a natural concept of Las Vegas computability on infinite objects is more powerful than mere oracle access to a Martin-Löf random object. As a concrete problem that is Las Vegas computable but not computable with access to a Martin-Löf random oracle we study the problem of finding Nash equilibria.
Cite as

Vasco Brattka, Guido Gherardi, and Rupert Hölzl. Las Vegas Computability and Algorithmic Randomness. In 32nd International Symposium on Theoretical Aspects of Computer Science (STACS 2015). Leibniz International Proceedings in Informatics (LIPIcs), Volume 30, pp. 130-142, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

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@InProceedings{brattka_et_al:LIPIcs.STACS.2015.130,
  author =	{Brattka, Vasco and Gherardi, Guido and H\"{o}lzl, Rupert},
  title =	{{Las Vegas Computability and Algorithmic Randomness}},
  booktitle =	{32nd International Symposium on Theoretical Aspects of Computer Science (STACS 2015)},
  pages =	{130--142},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-78-1},
  ISSN =	{1868-8969},
  year =	{2015},
  volume =	{30},
  editor =	{Mayr, Ernst W. and Ollinger, Nicolas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2015.130},
  URN =		{urn:nbn:de:0030-drops-49093},
  doi =		{10.4230/LIPIcs.STACS.2015.130},
  annote =	{Keywords: Weihrauch degrees, weak weak K\"{o}nig's lemma, Las Vegas computability, algorithmic randomness, Nash equilibria}
}
Document
DOI: 10.4230/LIPIcs.STACS.2015.420
Inductive Inference and Reverse Mathematics

Authors: Rupert Hölzl, Sanjay Jain, and Frank Stephan

Published in: LIPIcs, Volume 30, 32nd International Symposium on Theoretical Aspects of Computer Science (STACS 2015)

Abstract
The present work investigates inductive inference from the perspective of reverse mathematics. Reverse mathematics is a framework which relates the proof strength of theorems and axioms throughout many areas of mathematics in an interdisciplinary way. The present work looks at basic notions of learnability including Angluin's tell-tale condition and its variants for learning in the limit and for conservative learning. Furthermore, the more general criterion of partial learning is investigated. These notions are studied in the reverse mathematics context for uniformly and weakly represented families of languages. The results are stated in terms of axioms referring to domination and induction strength.
Cite as

Rupert Hölzl, Sanjay Jain, and Frank Stephan. Inductive Inference and Reverse Mathematics. In 32nd International Symposium on Theoretical Aspects of Computer Science (STACS 2015). Leibniz International Proceedings in Informatics (LIPIcs), Volume 30, pp. 420-433, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

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@InProceedings{holzl_et_al:LIPIcs.STACS.2015.420,
  author =	{H\"{o}lzl, Rupert and Jain, Sanjay and Stephan, Frank},
  title =	{{Inductive Inference and Reverse Mathematics}},
  booktitle =	{32nd International Symposium on Theoretical Aspects of Computer Science (STACS 2015)},
  pages =	{420--433},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-78-1},
  ISSN =	{1868-8969},
  year =	{2015},
  volume =	{30},
  editor =	{Mayr, Ernst W. and Ollinger, Nicolas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2015.420},
  URN =		{urn:nbn:de:0030-drops-49324},
  doi =		{10.4230/LIPIcs.STACS.2015.420},
  annote =	{Keywords: reverse mathematics, recursion theory, inductive inference, learning from positive data}
}
Document
DOI: 10.4230/LIPIcs.STACS.2012.543
The Denjoy alternative for computable functions

Authors: Laurent Bienvenu, Rupert Hölzl, Joseph S. Miller, and André Nies

Published in: LIPIcs, Volume 14, 29th International Symposium on Theoretical Aspects of Computer Science (STACS 2012)

Abstract
The Denjoy-Young-Saks Theorem from classical analysis states that for an arbitrary function f:R->R, the Denjoy alternative holds outside a null set, i.e., for almost every real x, either the derivative of f exists at x, or the derivative fails to exist in the worst possible way: the limit superior of the slopes around x equals +infinity, and the limit inferior -infinity. Algorithmic randomness allows us to define randomness notions giving rise to different concepts of almost everywhere. It is then natural to wonder which of these concepts corresponds to the almost everywhere notion appearing in the Denjoy-Young-Saks theorem. To answer this question Demuth investigated effective versions of the theorem and proved that Demuth randomness is strong enough to ensure the Denjoy alternative for Markov computable functions. In this paper, we show that the set of these points is indeed strictly bigger than the set of Demuth random reals - showing that Demuth's sufficient condition was too strong - and moreover is incomparable with Martin-Löf randomness; meaning in particular that it does not correspond to any known set of random reals. To prove these two theorems, we study density-type theorems, such as the Lebesgue density theorem and obtain results of independent interest. We show for example that the classical notion of Lebesgue density can be characterized by the only very recently defined notion of difference randomness. This is to our knowledge the first analytical characterization of difference randomness. We also consider the concept of porous points, a special type of Lebesgue nondensity points that are well-behaved in the sense that the "density holes" around the point are continuous intervals whose length follows a certain systematic rule. An essential part of our proof will be to argue that porous points of effectively closed classes can never be difference random.
Cite as

Laurent Bienvenu, Rupert Hölzl, Joseph S. Miller, and André Nies. The Denjoy alternative for computable functions. In 29th International Symposium on Theoretical Aspects of Computer Science (STACS 2012). Leibniz International Proceedings in Informatics (LIPIcs), Volume 14, pp. 543-554, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@InProceedings{bienvenu_et_al:LIPIcs.STACS.2012.543,
  author =	{Bienvenu, Laurent and H\"{o}lzl, Rupert and Miller, Joseph S. and Nies, Andr\'{e}},
  title =	{{The Denjoy alternative for computable functions}},
  booktitle =	{29th International Symposium on Theoretical Aspects of Computer Science (STACS 2012)},
  pages =	{543--554},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-35-4},
  ISSN =	{1868-8969},
  year =	{2012},
  volume =	{14},
  editor =	{D\"{u}rr, Christoph and Wilke, Thomas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2012.543},
  URN =		{urn:nbn:de:0030-drops-34095},
  doi =		{10.4230/LIPIcs.STACS.2012.543},
  annote =	{Keywords: Differentiability, Denjoy alternative, density, porosity, randomness}
}
Document
DOI: 10.4230/OASIcs.CCA.2009.2260
Separations of Non-monotonic Randomness Notions

Authors: Laurent Bienvenu, Rupert Hölzl, Thorsten Kräling, and Wolfgang Merkle

Published in: OASIcs, Volume 11, 6th International Conference on Computability and Complexity in Analysis (CCA'09) (2009)

Abstract
In the theory of algorithmic randomness, several notions of random sequence are defined via a game-theoretic approach, and the notions that received most attention are perhaps Martin-L\"of randomness and computable randomness. The latter notion was introduced by Schnorr and is rather natural: an infinite binary sequence is computably random if no total computable strategy succeeds on it by betting on bits in order. However, computably random sequences can have properties that one may consider to be incompatible with being random, in particular, there are computably random sequences that are highly compressible. The concept of Martin-L\"of randomness is much better behaved in this and other respects, on the other hand its definition in terms of martingales is considerably less natural. Muchnik, elaborating on ideas of Kolmogorov and Loveland, refined Schnorr's model by also allowing non-monotonic strategies, i.e.\ strategies that do not bet on bits in order. The subsequent ``non-monotonic'' notion of randomness, now called Kolmogorov-Loveland-randomness, has been shown to be quite close to Martin-L\"of randomness, but whether these two classes coincide remains a fundamental open question. In order to get a better understanding of non-monotonic randomness notions, Miller and Nies introduced some interesting intermediate concepts, where one only allows non-adaptive strategies, i.e., strategies that can still bet non-monotonically, but such that the sequence of betting positions is known in advance (and computable). Recently, these notions were shown by Kastermans and Lempp to differ from Martin-L\"of randomness. We continue the study of the non-monotonic randomness notions introduced by Miller and Nies and obtain results about the Kolmogorov complexities of initial segments that may and may not occur for such sequences, where these results then imply a complete classification of these randomness notions by order of strength.
Cite as

Laurent Bienvenu, Rupert Hölzl, Thorsten Kräling, and Wolfgang Merkle. Separations of Non-monotonic Randomness Notions. In 6th International Conference on Computability and Complexity in Analysis (CCA'09). Open Access Series in Informatics (OASIcs), Volume 11, pp. 71-82, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{bienvenu_et_al:OASIcs.CCA.2009.2260,
  author =	{Bienvenu, Laurent and H\"{o}lzl, Rupert and Kr\"{a}ling, Thorsten and Merkle, Wolfgang},
  title =	{{Separations of Non-monotonic Randomness Notions}},
  booktitle =	{6th International Conference on Computability and Complexity in Analysis (CCA'09)},
  pages =	{71--82},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-12-5},
  ISSN =	{2190-6807},
  year =	{2009},
  volume =	{11},
  editor =	{Bauer, Andrej and Hertling, Peter and Ko, Ker-I},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.CCA.2009.2260},
  URN =		{urn:nbn:de:0030-drops-22601},
  doi =		{10.4230/OASIcs.CCA.2009.2260},
  annote =	{Keywords: Martin-L\"{o}f randomness, Kolmogorov-Loveland randomness, Kolmogorov complexity, martingales, betting strategies}
}
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