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Russian Mathematical Surveys, 1970, Volume 25, Issue 6, Pages 83–124
DOI: https://doi.org/10.1070/RM1970v025n06ABEH001269
(Mi rm5428)
 

This article is cited in 415 scientific papers (total in 415 papers)

The complexity of finite objects and the development of the concepts of information and randomness by means of the theory of algorithms

A. K. Zvonkin, L. A. Levin
References:
Abstract: In 1964 Kolmogorov introduced the concept of the complexity of a finite object (for instance, the words in a certain alphabet). He defined complexity as the minimum number of binary signs containing all the information about a given object that are sufficient for its recovery (decoding). This definition depends essentially on the method of decoding. However, by means of the general theory of algorithms, Kolmogorov was able to give an invariant (universal) definition of complexity. Related concepts were investigated by Solomonoff (U.S.A.) and Markov. Using the concept of complexity, Kolmogorov gave definitions of the quantity of information in finite objects and of the concept of a random sequence (which was then defined more precisely by Martin-Löf). Afterwards, this circle of questions developed rapidly. In particular, an interesting development took place of the ideas of Markov on the application of the concept of complexity to the study of quantitative questions in the theory of algorithms. The present article is a survey of the fundamental results connected with the brief remarks above.
Received: 07.08.1970
Bibliographic databases:
Document Type: Article
UDC: 519.24+517.11+519.9
MSC: 68Q30, 94B35
Language: English
Original paper language: Russian
Citation: A. K. Zvonkin, 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 (1970), 83–124
Citation in format AMSBIB
\Bibitem{ZvoLev70}
\by A.~K.~Zvonkin, L.~A.~Levin
\paper The complexity of finite objects and the development of the concepts of information and randomness by means of the theory of algorithms
\jour Russian Math. Surveys
\yr 1970
\vol 25
\issue 6
\pages 83--124
\mathnet{http://mi.mathnet.ru/eng/rm5428}
\crossref{https://doi.org/10.1070/RM1970v025n06ABEH001269}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=307889}
\zmath{https://zbmath.org/?q=an:0222.02027}
Linking options:
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  • https://doi.org/10.1070/RM1970v025n06ABEH001269
  • https://www.mathnet.ru/eng/rm/v25/i6/p85
  • This publication is cited in the following 415 articles:
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    3. Ming Li, “Caging AI”, J. Comput. Sci. Technol., 40:1 (2025), 1  crossref
    4. Mingyang Li, Jan Reimann, “Turing degrees and randomness for continuous measures”, Arch. Math. Logic, 63:1-2 (2024), 39  crossref
    5. Markus Pantsar, “Theorem proving in artificial neural networks: new frontiers in mathematical AI”, Euro Jnl Phil Sci, 14:1 (2024)  crossref
    6. Mariano Lemus, Ricardo Faleiro, Paulo Mateus, Nikola Paunković, André Souto, “Quantum Kolmogorov complexity and quantum correlations in deterministic-control quantum Turing machines”, Quantum, 8 (2024), 1230  crossref
    7. Emirhan Gürpιnar, Andrei Romashchenko, “Communication Complexity of the Secret Key Agreement in Algorithmic Information Theory”, ACM Trans. Comput. Theory, 2024  crossref
    8. Zoe Leyva-Acosta, Eduardo Acuña Yeomans, Francisco Hernandez-Quiroz, “An Additively Optimal Interpreter for Approximating Kolmogorov Prefix Complexity”, Entropy, 26:9 (2024), 802  crossref
    9. Shuichi Hirahara, Zhenjian Lu, Mikito Nanashima, 2024 IEEE 65th Annual Symposium on Foundations of Computer Science (FOCS), 2024, 369  crossref
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    12. Bruno Bauwens*, Marius Zimand, “Universal almost Optimal Compression and Slepian-wolf Coding in Probabilistic Polynomial Time”, J. ACM, 70:2 (2023), 1  crossref
    13. Shuichi Hirahara, Rahul Ilango, Zhenjian Lu, Mikito Nanashima, Igor C. Oliveira, Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023, 1039  crossref
    14. George Barmpalias, Alexander Shen, “The Kučera–Gács theorem revisited by Levin”, Theoretical Computer Science, 947 (2023), 113693  crossref
    15. Laurent Beaudoin, Loïca Avanthey, “How to help digital-native students to successfully take control of their learning: A return of 8 years of experience on a computer science e-learning platform in higher education”, Educ Inf Technol, 28:5 (2023), 5421  crossref
    16. Yanyi Liu, Rafael Pass, Lecture Notes in Computer Science, 14082, Advances in Cryptology – CRYPTO 2023, 2023, 645  crossref
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    19. Adam Case, Christopher P. Porter, “The Intersection of Algorithmically Random Closed Sets and Effective Dimension”, ACM Trans. Comput. Logic, 23:4 (2022), 1  crossref
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    Citing articles in Google Scholar: Russian citations, English citations
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