Andrej Muchnik, Alexej Semenov

Mikhail V. Vyugin

C.H.~Bennett, P.~G\'acs, M.~Li, P.M.B.~Vit\'anyi, and W.H.~Zurek

have defined information distance between two strings $x$, $y$

as

$$

d(x,y)=\max\{ K(x|y), K(y|x) \}

$$

where $K(x|y)$ is the conditional Kolmogorov complexity.

It is easy to see that for any string $x$ and any integer $n$

there is a string $y$ ...
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Andrei Romashchenko, Alexander Shen, Nikolay Vereshchagin

The very first Kolmogorov's paper on algorithmic

information theory was entitled `Three approaches to the

definition of the quantity of information'. These three

approaches were called combinatorial, probabilistic and

algorithmic. Trying to establish formal connections

between combinatorial and algorithmic approaches, we

prove that any ...
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Nikolay Vereshchagin, Mikhail V. Vyugin

A string $p$ is called a program to compute $y$ given $x$

if $U(p,x)=y$, where $U$ denotes universal programming language.

Kolmogorov complexity $K(y|x)$ of $y$ relative to $x$

is defined as minimum length of

a program to compute $y$ given $x$.

Let $K(x)$ denote $K(x|\text{empty string})$

(Kolmogorov complexity of $x$) ...
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Mikhail V. Vyugin, Vladimir Vyugin

Predictive complexity is a generalization of Kolmogorov complexity

which gives a lower bound to ability of any algorithm to predict

elements of a sequence of outcomes. A variety of types of loss

functions makes it interesting to study relations between corresponding

predictive complexities.

Non-linear inequalities between predictive complexity of ... more >>>

Elvira Mayordomo

We obtain the following full characterization of constructive dimension

in terms of algorithmic information content. For every sequence A,

cdim(A)=liminf_n (K(A[0..n-1])/n.

Nikolay Vereshchagin

We present a simplified proof of Solovay-Calude-Coles theorem

stating that there is an enumerable undecidable set with the

following property: prefix

complexity of its initial segment of length n is bounded by prefix

complexity of n (up to an additive constant).

Nikolay Vereshchagin

Assume that for almost all n Kolmogorov complexity

of a string x conditional to n is less than m.

We prove that in this case

there is a program of size m+O(1) that given any sufficiently large

n outputs x.

Bruno Durand, Alexander Shen, Nikolay Vereshchagin

We study different notions of descriptive complexity of

computable sequences. Our main result states that if for almost all

n the Kolmogorov complexity of the n-prefix of an infinite

binary sequence x conditional to n

is less than m then there is a program of length

m^2+O(1) that for ...
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Alexander Shen, Nikolay Vereshchagin

We define Kolmogorov complexity of a set of strings as the minimal

Kolmogorov complexity of its element. Consider three logical

operations on sets going back to Kolmogorov

and Kleene:

(A OR B) is the direct sum of A,B,

(A AND B) is the cartesian product of A,B,

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Andrej Muchnik, Nikolay Vereshchagin

We invistigate what is the minimal length of

a program mapping A to B and at the same time

mapping C to D (where A,B,C,D are binary strings). We prove that

it cannot be expressed

in terms of Kolmogorv complexity of A,B,C,D, their pairs (A,B), (A,C),

..., their ...
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Boris Ryabko

The problem of predicting a sequence $x_1, x_2,.... $ where each $x_i$ belongs

to a finite alphabet $A$ is considered. Each letter $x_{t+1}$ is predicted

using information on the word $x_1, x_2, ...., x_t $ only. We use the game

theoretical interpretation which can be traced to Laplace where there ...
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Eric Allender, Harry Buhrman, Michal Koucky, Detlef Ronneburger, Dieter van Melkebeek

We consider sets of strings with high Kolmogorov complexity, mainly

in resource-bounded settings but also in the traditional

recursion-theoretic sense. We present efficient reductions, showing

that these sets are hard and complete for various complexity classes.

In particular, in addition to the usual Kolmogorov complexity measure

K, ...
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Troy Lee, Dieter van Melkebeek, Harry Buhrman

The language compression problem asks for succinct descriptions of

the strings in a language A such that the strings can be efficiently

recovered from their description when given a membership oracle for

A. We study randomized and nondeterministic decompression schemes

and investigate how close we can get to the information ...
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Richard Beigel, Harry Buhrman, Peter Fejer, Lance Fortnow, Piotr Grabowski, Luc Longpré, Andrej Muchnik, Frank Stephan, Leen Torenvliet

A recursive enumerator for a function $h$ is an algorithm $f$ which

enumerates for an input $x$ finitely many elements including $h(x)$.

$f$ is an $k(n)$-enumerator if for every input $x$ of length $n$, $h(x)$

is among the first $k(n)$ elements enumerated by $f$.

If there is a $k(n)$-enumerator for ...
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Nikolay Vereshchagin

Solovay has proven that

the minimal length of a program enumerating a set A

is upper bounded by 3 times the absolute value of the

logarithm of the

probability that a random program will enumerate A.

It is unknown whether one can replace the constant

3 by a smaller constant.

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Troy Lee, Andrei Romashchenko

The information contained in a string $x$ about a string $y$

is defined as the difference between the Kolmogorov complexity

of $y$ and the conditional Kolmogorov complexity of $y$ given $x$,

i.e., $I(x:y)=\C(y)-\C(y|x)$. From the well-known Kolmogorov--Levin Theorem it follows that $I(x:y)$ is symmetric up to a small ...
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Eric Allender, Harry Buhrman, Michal Koucky

We investigate the question of whether one can characterize complexity

classes (such as PSPACE or NEXP) in terms of efficient

reducibility to the set of Kolmogorov-random strings R_C.

We show that this question cannot be posed without explicitly dealing

with issues raised by the choice of universal

machine in the ...
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Andrej Muchnik, Alexander Shen, Nikolay Vereshchagin, Mikhail V. Vyugin

Let a program p on input a output b. We are looking for a

shorter program p' having the same property (p'(a)=b). In

addition, we want p' to be simple conditional to p (this

means that the conditional Kolmogorov complexity K(p'|p) is

negligible). In the present paper, we prove that ...
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Lance Fortnow, Troy Lee, Nikolay Vereshchagin

We introduce the study of Kolmogorov complexity with error. For a

metric d, we define C_a(x) to be the length of a shortest

program p which prints a string y such that d(x,y) \le a. We

also study a conditional version of this measure C_{a,b}(x|y)

where the task is, given ...
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Harry Buhrman, Lance Fortnow, Ilan Newman, Nikolay Vereshchagin

How much do we have to change a string to increase its Kolmogorov complexity. We show that we can

increase the complexity of any non-random string of length n by flipping O(sqrt(n)) bits and some strings

require

Omega(sqrt(n)) bit flips. For a given m, we also give bounds for ...
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Lance Fortnow, John Hitchcock, A. Pavan, Vinodchandran Variyam, Fengming Wang

We apply recent results on extracting randomness from independent

sources to ``extract'' Kolmogorov complexity. For any $\alpha,

\epsilon > 0$, given a string $x$ with $K(x) > \alpha|x|$, we show

how to use a constant number of advice bits to efficiently

compute another string $y$, $|y|=\Omega(|x|)$, with $K(y) >

(1-\epsilon)|y|$. ...
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Lance Fortnow, Luis Antunes

We show that under a reasonable hardness assumptions, the time-bounded Kolmogorov distribution is a universal samplable distribution. Under the same assumption we exactly characterize the worst-case running time of languages that are in average polynomial-time over all P-samplable distributions.

more >>>Alexander Shen

Multisource information theory in Shannon setting is well known. In this article we try to develop its algorithmic information theory counterpart and use it as the general framework for many interesting questions about Kolmogorov complexity.

more >>>Maria Lopez-Valdes

We define a new discrete version of scaled dimension and we find

connections between the scaled dimension of a string and its Kolmogorov

complexity and predictability. We give a new characterization

of constructive scaled dimension by Kolmogorov complexity, and prove

a new result about scaled dimension and prediction.

Ludwig Staiger

We present a brief survey of results on relations between the Kolmogorov

complexity of infinite strings and several measures of information content

(dimensions) known from dimension theory, information theory or fractal

geometry.

Special emphasis is laid on bounds on the complexity of strings in

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David Doty

A dimension extractor is an algorithm designed to increase the effective dimension -- i.e., the computational information density -- of an infinite sequence. A constructive dimension extractor is exhibited by showing that every sequence of positive constructive dimension is Turing equivalent to a sequence of constructive strong dimension arbitrarily ... more >>>

Luis Antunes, Lance Fortnow, Alexandre Pinto, Andre Souto

Antunes, Fortnow, van Melkebeek and Vinodchandran captured the

notion of non-random information by computational depth, the

difference between the polynomial-time-bounded Kolmogorov

complexity and traditional Kolmogorov complexity We show how to

find satisfying assignments for formulas that have at least one

assignment of logarithmic depth. The converse holds under a

standard ...
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Marc Kaplan, Sophie Laplante

A very important problem in quantum communication complexity is to show that there is, or isn?t, an exponential gap between randomized and quantum complexity for a total function. There are currently no clear candidate functions for such a separation; and there are fewer and fewer randomized lower bound techniques that ... more >>>

Eric Allender, Michal Koucky, Detlef Ronneburger, Sambuddha Roy

We continue an investigation into resource-bounded Kolmogorov complexity \cite{abkmr}, which highlights the close connections between circuit complexity and Levin's time-bounded Kolmogorov complexity measure Kt (and other measures with a similar flavor), and also exploits derandomization techniques to provide new insights regarding Kolmogorov complexity.

The Kolmogorov measures that have been ...
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John Hitchcock, A. Pavan, Vinodchandran Variyam

We clarify the role of Kolmogorov complexity in the area of randomness extraction. We show that a computable function is an almost randomness extractor if and only if it is a Kolmogorov complexity

extractor, thus establishing a fundamental equivalence between two forms of extraction studied in the literature: Kolmogorov extraction

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Eric Allender

It is a trivial observation that every decidable set has strings of length $n$ with Kolmogorov complexity $\log n + O(1)$ if it has any strings of length $n$ at all. Things become much more interesting when one asks whether a similar property holds when one

considers *resource-bounded* Kolmogorov complexity. ...
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Scott Aaronson

In a sampling problem, we are given an input $x\in\left\{0,1\right\} ^{n}$, and asked to sample approximately from a probability

distribution $D_{x}$ over poly(n)-bit strings. In a search problem, we are given an input

$x\in\left\{ 0,1\right\} ^{n}$, and asked to find a member of a nonempty set

$A_{x}$ with high probability. ...
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Eric Allender, Luke Friedman, William Gasarch

In this paper we give an exposition of a theorem by Muchnik and Positselsky, showing that there is a universal prefix Turing machine U, with the property that there is no truth-table reduction from the halting problem to the set {(x,i) : there is a description d of length at ... more >>>

Eric Allender, Luke Friedman, William Gasarch

Let C(x) and K(x) denote plain and prefix Kolmogorov complexity, respectively, and let R_C and R_K denote the sets of strings that are ``random'' according to these measures; both R_K and R_C are undecidable. Earlier work has shown that every set in NEXP is in NP relative to both R_K ... more >>>

Antoine Taveneaux

In \cite{shenpapier82}, it is shown that four basic functional properties are enough to characterize plain Kolmogorov complexity, hence obtaining an axiomatic characterization of this notion. In this paper, we try to extend this work, both by looking at alternative axiomatic systems for plain complexity and by considering potential axiomatic systems ... more >>>

mohammad iftekhar husain, steve ko, Atri Rudra, steve uurtamo

We consider the following problem that arises in outsourced storage: a user stores her data $x$ on a remote server but wants to audit the server at some later point to make sure it actually did store $x$. The goal is to design a (randomized) verification protocol that has the ... more >>>

Eric Allender, George Davie, Luke Friedman, Samuel Hopkins, Iddo Tzameret

Can complexity classes be characterized in terms of efficient reducibility to the (undecidable) set of Kolmogorov-random strings? Although this might seem improbable, a series of papers has recently provided evidence that this may be the case. In particular, it is known that there is a class of problems $C$ defined ... more >>>

Eric Allender, Harry Buhrman, Luke Friedman, Bruno Loff

This paper is motivated by a conjecture that BPP can be characterized in terms of polynomial-time nonadaptive reductions to the set of Kolmogorov-random strings. In this paper we show that an approach laid out by [Allender et al] to settle this conjecture cannot succeed without significant alteration, but that it ... more >>>

Bruno Bauwens, Anton Makhlin, Nikolay Vereshchagin, Marius Zimand

Given a machine $U$, a $c$-short program for $x$ is a string $p$ such that $U(p)=x$ and the length of $p$ is bounded by $c$ + (the length of a shortest program for $x$). We show that for any universal machine, it is possible to compute in polynomial time on ... more >>>

Jack H. Lutz

A 1976 theorem of Chaitin, strengthening a 1969 theorem of Meyer,says that infinitely many lengths n have a paucity of trivial strings (only a bounded number of strings of length n having trivially low plain Kolmogorov complexities). We use the probabilistic method to give a new proof of this fact. ... more >>>

Adam Case, Jack H. Lutz

We define the lower and upper mutual dimensions $mdim(x:y)$ and $Mdim(x:y)$ between any two points $x$ and $y$ in Euclidean space. Intuitively these are the lower and upper densities of the algorithmic information shared by $x$ and $y$. We show that these quantities satisfy the main desiderata for a satisfactory ... more >>>

Eric Allender, Dhiraj Holden, Valentine Kabanets

We consider variants of the Minimum Circuit Size Problem MCSP, where the goal is to minimize the size of oracle circuits computing a given function. When the oracle is QBF, the resulting problem MCSP$^{QBF}$ is known to be complete for PSPACE under ZPP reductions. We show that it is not ... more >>>

Juraj Hromkovic

Mathematics was developed as a strong research instrument with fully verifiable argumentations. We call any formal theory based on syntactic rules that enables to algorithmically verify for any given text whether it is a proof or not algorithmically verifiable mathematics (AV-mathematics for short). We say that a decision problem L ... more >>>

Alexey Milovanov, Nikolay Vereshchagin

A fundamental notion in Algorithmic Statistics is that of a stochastic object, i.e., an object having a simple plausible explanation. Informally, a probability distribution is a plausible explanation for $x$ if it looks likely that $x$ was drawn at random with respect to that distribution. In this paper, we ... more >>>

Eric Allender, Shuichi Hirahara

The Minimum Circuit Size Problem (MCSP) and a related problem (MKTP) that deals with time-bounded Kolmogorov complexity are prominent candidates for NP-intermediate status. We show that, under very modest cryptographic assumptions (such as the existence of one-way functions), the problem of approximating the minimum circuit size (or time-bounded Kolmogorov complexity) ... more >>>

Andrei Romashchenko, Marius Zimand

We show that the mutual information, in the sense of Kolmogorov complexity, of any pair of strings

$x$ and $y$ is equal, up to logarithmic precision, to the length of the longest shared secret key that

two parties, one having $x$ and the complexity profile of the pair and the ...
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