skip to main content
10.1145/2603088.2603114acmconferencesArticle/Chapter ViewAbstractPublication PageslicsConference Proceedingsconference-collections
research-article

A quest for algorithmically random infinite structures

Published:14 July 2014Publication History

ABSTRACT

The last two decades have witnessed significant advances in the investigation of algorithmic randomness, such as Martin-Löf randomness, of infinite strings. In spite of much work, research on randomness of infinite strings has excluded the investigation of algorithmic randomness for infinite algebraic structures. The main obstacle in introducing algorithmic randomness for infinite structures is that many classes of infinite structures lack measure. More precisely, it is unclear how one would define a meaningful measure through which it would be possible to introduce algorithmic randomness for infinite structures. In this paper, we overcome this obstacle by proposing a limited amount of finiteness conditions on various classes of infinite structures. These conditions will enable us to introduce measure and, as a consequence, reason about algorithmic randomness. Our classes include finitely generated universal algebras, connected graphs and tress of bounded degree, and monoids. For all these classes one can introduce algorithmic randomness concepts and prove existence of random structures. In particular, we prove that Martin-Lóf random universal algebras, graphs, trees, and monoids exist. In the case of trees we show a stronger result that Martin-Löf random computably enumerable trees exist.

References

  1. V. Bratka, J. Miller and A. Nies. Randomness and differentiability. Manuscript, 2012.Google ScholarGoogle Scholar
  2. C. S. Calude. Information and Randomness - An Algorithmic Perspective. 2nd Edition, Revised and Extended, Springer-Verlag, Berlin, 2002. 485 pp. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. G. J. Chaitin. On the length of programs for computing finite binary sequences: statistical considerations, Journal of the ACM, 16:145159, 1969. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. R. Downey and D. Hirschfeldt. Algorithmic Randomness and Complexity, Theory and Applications of Computability, Springer, New York, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. G. Grätzer, Universal Algebra, revised reprint of the second edition, Springer, New York, 2008.Google ScholarGoogle Scholar
  6. H. Buhrman, M. Li, J. Tromp, and P. Vitanyi. Kolmogorov random graphs and the incompressibility method. SIAM J. Comput., 29(2), 590599. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. W. Hodges. Model Theory. Encyclopaedia of Mathematics and Its Applications, No 42. Cambridge University Press, 1993.Google ScholarGoogle Scholar
  8. A. Kolmogorov. Three approaches to the quantitative definition of information, Problems of Information Transmission 1, p.1--7, 1965.Google ScholarGoogle Scholar
  9. M. Li and P. Vitanyi. An introduction to Kolmogorov complexity and its applications, Springer-Verlag, 3rd Edition 2008 (xx+792 pp). Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. P. Martin-Löf. The definition of random sequences, Information and Control 9(6), 602--619, 1966.Google ScholarGoogle ScholarCross RefCross Ref
  11. R. von Mises. Grundlagen der Wahrscheinlichkeitsrechnung, Mathematische Zeitschrift 5(191), 5299, 1919.Google ScholarGoogle Scholar
  12. A. Nies. Computability and Randomness, Oxford University Press, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. A. Nies. Personal communication.Google ScholarGoogle Scholar
  14. C. P. Schnorr. A unified approach to the definition of random sequences, Mathematical Systems Theory 5(3):246258 (1971).Google ScholarGoogle ScholarCross RefCross Ref
  15. C. P. Schnorr. The process complexity and effective random tests, Proceedings of the fourth ACM symposium of Theory of Computing, Denver, Colorado, May 13, 1972. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. A. K. Zvonkin and L. A. Levin. The complexity of finite objects and the development of the concepts of information and randomness by means of the theory of algorithms. Russian Math. Surveys, 25(6):83--124, 1970.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. A quest for algorithmically random infinite structures

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          CSL-LICS '14: Proceedings of the Joint Meeting of the Twenty-Third EACSL Annual Conference on Computer Science Logic (CSL) and the Twenty-Ninth Annual ACM/IEEE Symposium on Logic in Computer Science (LICS)
          July 2014
          764 pages
          ISBN:9781450328869
          DOI:10.1145/2603088
          • Program Chairs:
          • Thomas Henzinger,
          • Dale Miller

          Copyright © 2014 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 14 July 2014

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article

          Acceptance Rates

          CSL-LICS '14 Paper Acceptance Rate74of212submissions,35%Overall Acceptance Rate143of386submissions,37%

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader