Randomness and imprecision: From supermartingales to randomness tests

IF 1 4区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS
Gert de Cooman, Floris Persiau, Jasper De Bock
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引用次数: 0

Abstract

We generalise the randomness test definitions in the literature for both the Martin-Löf and Schnorr randomness of a series of binary outcomes, in order to allow for interval-valued rather than merely precise forecasts for these outcomes, and prove that under some computability conditions on the forecasts, our definition of Martin-Löf test randomness is related to Levin's uniform randomness. We also show that these new randomness notions are, under some computability and non-degeneracy conditions on the forecasts, equivalent to the martingale-theoretic versions we introduced in earlier papers. In addition, we prove that our generalised notion of Martin-Löf randomness can be characterised by universal supermartingales and universal randomness tests.
随机性和不精确性:从上鞅到随机性检验
我们推广了文献中对于一系列二元结果的Martin-Löf和Schnorr随机性的随机性检验定义,以便允许对这些结果进行区间值预测而不仅仅是精确预测,并证明在预测的某些可计算条件下,我们对Martin-Löf检验随机性的定义与Levin的均匀随机性有关。我们还证明了这些新的随机性概念,在预测的一些可计算性和非退化性条件下,等价于我们在以前的论文中介绍的鞅理论版本。此外,我们还证明了Martin-Löf随机性的广义概念可以用普遍上鞅和普遍随机性检验来表征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Information and Computation
Information and Computation 工程技术-计算机:理论方法
CiteScore
2.30
自引率
0.00%
发文量
119
审稿时长
140 days
期刊介绍: Information and Computation welcomes original papers in all areas of theoretical computer science and computational applications of information theory. Survey articles of exceptional quality will also be considered. Particularly welcome are papers contributing new results in active theoretical areas such as -Biological computation and computational biology- Computational complexity- Computer theorem-proving- Concurrency and distributed process theory- Cryptographic theory- Data base theory- Decision problems in logic- Design and analysis of algorithms- Discrete optimization and mathematical programming- Inductive inference and learning theory- Logic & constraint programming- Program verification & model checking- Probabilistic & Quantum computation- Semantics of programming languages- Symbolic computation, lambda calculus, and rewriting systems- Types and typechecking
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