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Non-approximability of the Randomness Deficiency Function

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Book cover Computer Science – Theory and Applications (CSR 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3967))

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Abstract

Let x be a binary string of length n. Consider the set P x of all pairs of integers (a,b) such that the randomness deficiency of x in a finite set S of Kolmogorov complexity at most a is at most b. The paper [4] proves that there is no algorithm that for every given x upper semicomputes the minimal deficiency function β x (a) = min{b | (a,b) ∈ p x }with precision n/log4 n. We strengthen this result in two respects. First, we improve the precision to n/4. Second, we show that there is no algorithm that for every given x enumerates a set at distance at most n/4 from P x , which is easier than to upper semicompute the minimal deficiency function of x with the same accuracy.

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References

  1. Gács, P., Tromp, J., Vitányi, P.M.B.: Algorithmic statistics. IEEE Trans. Inform. Th. 47(6), 2443–2463 (2001)

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  2. Kolmogorov, A.N.: Three approaches to the quantitative definition of information. Problems Inform. Transmission 1(1), 1–7 (1965)

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  3. Li, M., Vitanyi, P.M.B.: An Intoduction to Kolmogorov Complexity and its Applications, 2nd edn. Springer, New York (1997)

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  4. Vereshchagin, N., Vitanyi, P.: Kolmogorov’s Structure Functions with an Application to the Foundations of Model Selection. IEEE Transactions on Information Theory 50(12), 3265–3290 (2004); Preliminary version: Proc. 47th IEEE Symp. Found. Comput. Sci., pp. 751–760 (2002)

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© 2006 Springer-Verlag Berlin Heidelberg

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Ustinov, M.A. (2006). Non-approximability of the Randomness Deficiency Function. In: Grigoriev, D., Harrison, J., Hirsch, E.A. (eds) Computer Science – Theory and Applications. CSR 2006. Lecture Notes in Computer Science, vol 3967. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11753728_37

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  • DOI: https://doi.org/10.1007/11753728_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34166-6

  • Online ISBN: 978-3-540-34168-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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