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An a priori semimeasure (also known as "algorithmic probability" or "the Solomonoff prior" in the context of inductive inference) is defined as the transformation, by a given universal monotone Turing machine, of the uniform measure on the…

Statistics Theory · Mathematics 2016-06-29 Tom F. Sterkenburg

Previously referred to as `miraculous' in the scientific literature because of its powerful properties and its wide application as optimal solution to the problem of induction/inference, (approximations to) Algorithmic Probability (AP) and…

Information Theory · Computer Science 2018-04-16 Hector Zenil , Liliana Badillo , Santiago Hernández-Orozco , Francisco Hernández-Quiroz

This expository paper advocates an approach to physics in which ``typicality" is identified with a suitable form of algorithmic randomness. To this end various theorems from mathematics and physics are reviewed. Their original versions…

Mathematical Physics · Physics 2023-09-06 Klaas Landsman

The concept of time emerges as an ordering structure in a classical statistical ensemble. Probability distributions $p_\tau(t)$ at a given time $t$ obtain by integrating out the past and future. We discuss all-time probability distributions…

High Energy Physics - Theory · Physics 2015-05-18 C. Wetterich

[Abridged] Some cosmological theories propose that the observable universe is a small part of a much larger universe in which parameters describing the low-energy laws of physics vary from region to region. How can we reasonably assess a…

Cosmology and Nongalactic Astrophysics · Physics 2026-02-04 Feraz Azhar , Alan H. Guth , Mohammad Hossein Namjoo

While Kolmogorov complexity is the accepted absolute measure of information content of an individual finite object, a similarly absolute notion is needed for the relation between an individual data sample and an individual model summarizing…

Statistics Theory · Mathematics 2007-07-16 Peter Gacs , John Tromp , Paul Vitanyi

For a broad class of input-output maps, arguments based on the coding theorem from algorithmic information theory (AIT) predict that simple (low Kolmogorov complexity) outputs are exponentially more likely to occur upon uniform random…

Data Analysis, Statistics and Probability · Physics 2019-10-03 Kamaludin Dingle , Guillermo Valle Pérez , Ard A. Louis

Physics is based on probabilities as fundamental entities of a mathematical description. Expectation values of observables are computed according to the classical statistical rule. The overall probability distribution for one world covers…

Quantum Physics · Physics 2024-10-28 C. Wetterich

As observers of the universe we are physical systems within it. If the universe is very large in space and/or time, the probability becomes significant that the data on which we base predictions is replicated at other locations in…

High Energy Physics - Theory · Physics 2015-05-18 Mark Srednicki , James Hartle

From the existence of an efficient quantum algorithm for factoring, it is likely that quantum computation is intrinsically more powerful than classical computation. At present, the best upper bound known for the power of quantum computation…

Quantum Physics · Physics 2015-09-14 Ciarán M. Lee , Jonathan Barrett

Consider the following prediction problem. Assume that there is a block box that produces bits according to some unknown computable distribution on the binary tree. We know first $n$ bits $x_1 x_2 \ldots x_n$. We want to know the…

Information Theory · Computer Science 2023-08-25 Alexey Milovanov

We discuss views about whether the universe can be rationally comprehended, starting with Plato, then Leibniz, and then the views of some distinguished scientists of the previous century. Based on this, we defend the thesis that…

History and Overview · Mathematics 2007-05-23 G. J. Chaitin

We present a general theory of quantum information processing devices, that can be applied to human decision makers, to atomic multimode registers, or to molecular high-spin registers. Our quantum decision theory is a generalization of the…

Quantum Physics · Physics 2009-11-13 V. I. Yukalov , D. Sornette

As observers of the universe we are quantum physical systems within it. If the universe is very large in space and/or time, the probability becomes significant that the data on which we base predictions is replicated at other locations in…

High Energy Physics - Theory · Physics 2013-05-29 Mark Srednicki , James Hartle

Consider a universal Turing machine that produces a partial or total function (or a binary stream), based on the answers to the binary queries that it makes during the computation. We study the probability that the machine will produce a…

Computational Complexity · Computer Science 2017-04-28 George Barmpalias , Douglas Cenzer , Christopher P. Porter

We construct universal prediction systems in the spirit of Popper's falsifiability and Kolmogorov complexity and randomness. These prediction systems do not depend on any statistical assumptions (but under the IID assumption they dominate,…

Machine Learning · Computer Science 2017-04-05 Vladimir Vovk , Dusko Pavlovic

We describe the universe as a single entangled ensemble of quantum particles. The total entropy of this world ensemble, which can be expressed as a sum of information, thermodynamic and entanglement components, is assumed to be always zero.…

General Physics · Physics 2018-05-15 Merab Gogberashvili

Quantum theory (QT) has been confirmed by numerous experiments, yet we still cannot fully grasp the meaning of the theory. As a consequence, the quantum world appears to us paradoxical. Here we shed new light on QT by having it follow from…

Quantum Physics · Physics 2019-02-12 Alessio Benavoli , Alessandro Facchini , Marco Zaffalon

Solomonoff unified Occam's razor and Epicurus' principle of multiple explanations to one elegant, formal, universal theory of inductive inference, which initiated the field of algorithmic information theory. His central result is that the…

Machine Learning · Computer Science 2008-06-26 Marcus Hutter

The notion of probability plays an important role in almost all areas of science and technology. In modern mathematics, however, probability theory means nothing other than measure theory, and the operational characterization of the notion…

Probability · Mathematics 2019-09-09 Kohtaro Tadaki
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