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Kolmogorov complexity theory is used to tell what the algorithmic informational content of a string is. It is defined as the length of the shortest program that describes the string. We present a programming language that can be used to…

Category Theory · Mathematics 2013-06-13 Noson S. Yanofsky

For every total recursive time bound $t$, a constant fraction of all compressible (low Kolmogorov complexity) strings is $t$-bounded incompressible (high time-bounded Kolmogorov complexity); there are uncountably many infinite sequences of…

Computational Complexity · Computer Science 2009-08-11 E. G. Daylight , W. M. Koolen , P. M. B. Vitanyi

We show how minimal elements of a stopping time $\sigma$-algebra can be expressed in terms of the minimal elements of the $\sigma$-algebra of the underlying filtration. This facilitates an intuitive interpretation of stopping time…

Probability · Mathematics 2015-01-30 Tom Fischer

Effective complexity measures the information content of the regularities of an object. It has been introduced by M. Gell-Mann and S. Lloyd to avoid some of the disadvantages of Kolmogorov complexity, also known as algorithmic information…

Information Theory · Computer Science 2010-11-22 Nihat Ay , Markus Mueller , Arleta Szkola

A practical measure for the complexity of sequences of symbols (``strings'') is introduced that is rooted in automata theory but avoids the problems of Kolmogorov-Chaitin complexity. This physical complexity can be estimated for ensembles…

adap-org · Physics 2009-10-28 C. Adami , N. J. Cerf

Through a straightforward Bayesian approach we show that under some general conditions a maximum running time, namely the number of discrete steps performed by a computer program during its execution, can be defined such that the…

History and Overview · Mathematics 2007-05-23 Germano D'Abramo

It is shown that the length of the algorithmic minimal sufficient statistic of a binary string x, either in a representation of a finite set, computable semimeasure, or a computable function, has a length larger than the computational depth…

Computational Complexity · Computer Science 2009-11-25 Bruno Bauwens

Diverse applications of Kolmogorov complexity to learning [CIKK16], circuit complexity [OPS19], cryptography [LP20], average-case complexity [Hir21], and proof search [Kra22] have been discovered in recent years. Since the running time of…

Computational Complexity · Computer Science 2022-05-31 Zhenjian Lu , Igor C. Oliveira

Inspired by Solomonoffs theory of inductive inference, we propose a prior based on circuit complexity. There are several advantages to this approach. First, it relies on a complexity measure that does not depend on the choice of UTM. There…

Machine Learning · Computer Science 2023-06-27 Cole Wyeth , Carl Sturtivant

Algorithms which learn environments represented by automata in the past have had complexity scaling with the number of states in the automaton, which can be exponentially large even for automata recognizing regular expressions with a small…

Formal Languages and Automata Theory · Computer Science 2024-05-13 Ali Cataltepe , Vanessa Kosoy

The main goal of this paper is to put some known results in a common perspective and to simplify their proofs. We start with a simple proof of a result from (Vereshchagin, 2002) saying that $\limsup_n\KS(x|n)$ (here $\KS(x|n)$ is…

Computational Complexity · Computer Science 2008-02-21 Laurent Bienvenu , Andrej Muchnik , Alexander Shen , Nikolay Vereshchagin

Joseph Miller [16] and independently Andre Nies, Frank Stephan and Sebastiaan Terwijn [18] gave a complexity characterization of 2-random sequences in terms of plain Kolmogorov complexity C: they are sequences that have infinitely many…

Information Theory · Computer Science 2013-10-22 Bruno Bauwens

According to Kolmogorov complexity, every finite binary string is compressible to a shortest code -- its information content -- from which it is effectively recoverable. We investigate the extent to which this holds for infinite binary…

Information Theory · Computer Science 2019-01-23 George Barmpalias , Andrew Lewis-Pye

String matching is the problem of deciding whether a given $n$-bit string contains a given $k$-bit pattern. We study the complexity of this problem in three settings. Communication complexity. For small $k$, we provide near-optimal upper…

Computational Complexity · Computer Science 2019-02-21 Alexander Golovnev , Mika Göös , Daniel Reichman , Igor Shinkar

The main goal of this article is to put some known results in a common perspective and to simplify their proofs. We start with a simple proof of a result of Vereshchagin saying that $\limsup_n C(x|n)$ equals $C^{0'}(x)$. Then we use the…

Logic · Mathematics 2012-04-03 Laurent Bienvenu , Andrej Muchnik , Alexander Shen , Nikolai Vereshchagin

We provide tight upper and lower bounds on the expected minimum Kolmogorov complexity of binary classifiers that are consistent with labeled samples. The expected size is not more than complexity of the target concept plus the conditional…

Computational Complexity · Computer Science 2022-02-04 Samuel Epstein

The difficulty of explaining non-local correlations in a fixed causal structure sheds new light on the old debate on whether space and time are to be seen as fundamental. Refraining from assuming space-time as given a priori has a number of…

Quantum Physics · Physics 2018-01-15 Ämin Baumeler , Stefan Wolf

We prove two lower bounds for stopping times of sequential tests between general composite nulls and alternatives. The first lower bound is for the setting where the type-1 error level $\alpha$ approaches zero, and equals $\log(1/\alpha)$…

Statistics Theory · Mathematics 2025-04-29 Shubhada Agrawal , Aaditya Ramdas

Nonterminal complexity of a context-free language is the smallest possible number of nonterminals in its generating grammar. While in general case nonterminal complexity computation problem is unsolvable, it can be computed for different…

Formal Languages and Automata Theory · Computer Science 2021-03-23 Dmitry Golubenko

Average-case analysis computes the complexity of an algorithm averaged over all possible inputs. Compared to worst-case analysis, it is more representative of the typical behavior of an algorithm, but remains largely unexplored in…

Optimization and Control · Mathematics 2021-10-05 Courtney Paquette , Bart van Merriënboer , Elliot Paquette , Fabian Pedregosa