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Kolmogorov-Loveland Stochasticity and Kolmogorov Complexity

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4393))

Abstract

Merkle et al. [11] that all Kolmogorov-Loveland stochastic infinite binary sequences have constructive Hausdorff dimension 1. In this paper, we go even further, showing that from an infinite sequence of dimension less than \(\mathcal{H}({1\over2}+\delta)\) (\(\mathcal{H}\) being the Shannon entropy function) one can extract by a selection rule a biased subsequence with bias at least δ. We also prove an analogous result for finite strings.

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References

  1. Ambos-Spies, K., et al.: Resource-bounded dense genericity, stochasticity, and weak randomness. In: Puech, C., Reischuk, R. (eds.) STACS 1996. LNCS, vol. 1046, pp. 63–74. Springer, Heidelberg (1996)

    Google Scholar 

  2. Asarin, E.: Some properties of Kolmogorov Δ-random sequences. Theory Probab. Appl. 32, 507–508 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  3. Downey, R., Hirschfeldt, D.: Algorithmic Randomness and complexity. Book in preparation

    Google Scholar 

  4. Downey, R., Merkle, W., Reimann, J.: Schnorr dimension. In: Cooper, S.B., Löwe, B., Torenvliet, L. (eds.) CiE 2005. LNCS, vol. 3526, pp. 6–105. Springer, Heidelberg (2005)

    Google Scholar 

  5. Durand, B., Vereshchagin, N.: Kolmogorov-Loveland stochasticity for finite strings. Information Processing Letters 91(6), 263–269 (2004)

    Article  MathSciNet  Google Scholar 

  6. Lutz, J.: Dimension in complexity classes. In: Proc. 15th Conference on Computational Complexity, pp. 158–169. IEEE Computer Society Press, Los Alamitos (2000)

    Chapter  Google Scholar 

  7. Lutz, J.: The dimensions of individual strings and sequences. Information and Computation 187(1), 49–79 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  8. Li, M., Vitanyi, P.: An introduction to Kolmogorov complexity and its applications, 2nd edn. Texts in Computer Science. Springer, Heidelberg (1997)

    MATH  Google Scholar 

  9. Mayordomo, E.: A Kolmogorov complexity characterization of constructive Hausdorff dimension. Information Processing Letters 84, 1–3 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  10. Merkle, W.: The Kolmogorov-Loveland stochastic sequences are not closed under selecting subsequences. Journal of Symbolic Logic 68, 1362–1376 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  11. Merkle, W., et al.: Kolmogorov-Loveland Randomness and Stochasticity. Ann. Pure Appl. Logic 138(1-3), 183–210 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  12. Muchnik, A.A., Semenov, A.L., Uspensky, V.A.: Mathematical metaphysics of randomness. Theor. Comput. Sci. 207(2), 263–317 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  13. Schnorr, C.P.: Zufälligkeit und Wahrscheinlichkeit. Lecture Notes in Mathematics, vol. 218. Springer, Berlin (1971)

    Book  MATH  Google Scholar 

  14. Shen, A.: On relations between different algorithmic definitions of randomness. Soviet Mathematics Doklady 38, 316–319 (1989)

    MathSciNet  MATH  Google Scholar 

  15. von Mises, R.: Grundlagen der Wahrscheinlichkeitsrechnung. Math. Z. 5, 52–99 (1919)

    Article  MathSciNet  Google Scholar 

  16. van Lambalgen, M.: Random sequences. Ph.D. thesis, Univ. of Amsterdam, Amsterdam (1987)

    Google Scholar 

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Wolfgang Thomas Pascal Weil

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Bienvenu, L. (2007). Kolmogorov-Loveland Stochasticity and Kolmogorov Complexity. In: Thomas, W., Weil, P. (eds) STACS 2007. STACS 2007. Lecture Notes in Computer Science, vol 4393. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70918-3_23

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  • DOI: https://doi.org/10.1007/978-3-540-70918-3_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-70917-6

  • Online ISBN: 978-3-540-70918-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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