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Every K-trivial set is computable from an incomplete Martin-L\"of random set, i.e., a Martin-L\"of random set that does not compute 0'.

Algorithmic randomness theory starts with a notion of an individual random object. To be reasonable, this notion should have some natural properties; in particular, an object should be random with respect to image distribution if and only…

Logic · Mathematics 2016-07-15 Laurent Bienvenu , Mathieu Hoyrup , Alexander Shen

Computing reachability probabilities is a fundamental problem in the analysis of probabilistic programs. This paper aims at a comprehensive and comparative account on various martingale-based methods for over- and under-approximating…

Programming Languages · Computer Science 2018-11-16 Toru Takisaka , Yuichiro Oyabu , Natsuki Urabe , Ichiro Hasuo

We show that a pair of Kolmogorov-Loveland betting strategies cannot win on every non-Martin-L\"of random sequence if either of the two following conditions is true: (I) There is an unbounded computable function $g$ such that both betting…

Information Theory · Computer Science 2023-01-02 Tomislav Petrović

We elaborate the notions of Martin-L\"of and Schnorr randomness for real numbers in terms of uniform distribution of sequences. We give a necessary condition for a real number to be Schnorr random expressed in terms of classical uniform…

Logic · Mathematics 2021-11-30 Verónica Becher , Serge Grigorieff

The field of algorithmic randomness studies what it means for infinite binary sequences to be random for some given uncertainty model. Classically, martingale-theoretic notions of such randomness involve precise uncertainty models, and it…

Probability · Mathematics 2022-10-10 Floris Persiau , Jasper De Bock , Gert de Cooman

In algorithmic randomness, when one wants to define a randomness notion with respect to some non-computable measure $\lambda $, a choice needs to be made. One approach is to allow randomness tests to access the measure $\lambda $ as an…

Logic · Mathematics 2014-08-14 Bjørn Kjos-Hanssen , Antoine Taveneaux , Neil Thapen

Supermartingales are here defined on a non-probabilistic setting and can be interpreted solely in terms of superhedging operations. The classical expectation operator is replaced by a pair of subadditive operators one of them providing a…

Probability · Mathematics 2023-12-26 C. Bender , S. E. Ferrando , K. Gajewski , A. L. Gonzalez

The van Lambalgen theorem is a surprising result in algorithmic information theory concerning the symmetry of relative randomness. It establishes that for any pair of infinite sequences $A$ and $B$, $B$ is Martin-L\"of random and $A$ is…

Computational Complexity · Computer Science 2019-11-07 Diptarka Chakraborty , Satyadev Nandakumar , Himanshu Shukla

We characterize the event of convergence of a local supermartingale. Conditions are given in terms of its predictable characteristics and quadratic variation. The notion of stationarily local integrability plays a key role.

Probability · Mathematics 2020-03-16 Martin Larsson , Johannes Ruf

A fruitful way of obtaining meaningful, possibly concrete, algorithmically random numbers is to consider a potential behaviour of a Turing machine and its probability with respect to a measure (or semi-measure) on the input space of binary…

Computational Complexity · Computer Science 2017-06-13 George Barmpalias , Douglas Cenzer , Christopher P. Porter

A semi-measure is a generalization of a probability measure obtained by relaxing the additivity requirement to super-additivity. We introduce and study several randomness notions for left-c.e. semi-measures, a natural class of effectively…

Logic · Mathematics 2017-10-18 Laurent Bienvenu , Rupert Hölzl , Christopher P. Porter , Paul Shafer

Stochastic exponentials are defined for semimartingales on stochastic intervals, and stochastic logarithms are defined for semimartingales, up to the first time the semimartingale hits zero continuously. In the case of (nonnegative) local…

Probability · Mathematics 2020-09-16 Martin Larsson , Johannes Ruf

We introduce a notion of computable randomness for infinite sequences that generalises the classical version in two important ways. First, our definition of computable randomness is associated with imprecise probability models, in the sense…

Probability · Mathematics 2020-09-23 Floris Persiau , Jasper De Bock , Gert de Cooman

We use the martingale-theoretic approach of game-theoretic probability to incorporate imprecision into the study of randomness. In particular, we define a notion of computable randomness associated with interval, rather than precise,…

Probability · Mathematics 2017-05-05 Gert de Cooman , Jasper De Bock

Current discrete randomness and information conservation inequalities are over total recursive functions, i.e. restricted to deterministic processing. This restriction implies that an algorithm can break algorithmic randomness conservation…

Computational Complexity · Computer Science 2013-10-15 Samuel Epstein

We study the problem of whether a betting-strategy can be decomposed into an equivalent set of simpler betting-strategies, such as betting-strategies that bet on a restricted set of stages or bet on a restricted of favorable outcomes. We…

Probability · Mathematics 2022-03-08 George Barmpalias , Lu Liu

An infinite bit sequence is called recursively random if no computable strategy betting along the sequence has unbounded capital. It is well-known that the property of recursive randomness is closed under computable permutations. We…

Logic · Mathematics 2017-09-27 Andre Nies , Frank Stephan

Can a probabilistic gambler get arbitrarily rich when all deterministic gamblers fail? We study this problem in the context of algorithmic randomness, introducing a new notion -- almost everywhere computable randomness. A binary sequence…

Logic · Mathematics 2021-12-09 Laurent Bienvenu , Valentino Delle Rose , Tomasz Steifer

Betting strategies are often expressed formally as martingales. A martingale is called integer-valued if each bet must be an integer value. Integer-valued strategies correspond to the fact that in most betting situations, there is a minimum…

Computer Science and Game Theory · Computer Science 2015-05-21 George Barmpalias , Rod G. Downey , Michael McInerney