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Bayesian Inference is a powerful approach to data analysis that is based almost entirely on probability theory. In this approach, probabilities model {\it uncertainty} rather than randomness or variability. This thesis is composed of a…

Astrophysics · Physics 2008-09-08 Brendon J. Brewer

The theory of regularity is a philosophical perspective in which laws of nature are just descriptions, that is to say, laws of nature do not govern the world. Moreover, according to the theory of regularity, the number of laws of nature…

History and Philosophy of Physics · Physics 2024-03-05 Juliano C. S. Neves

Common knowledge/belief in rationality is the traditional standard assumption in analysing interaction among agents. This paper proposes a graph-based language for capturing significantly more complicated structures of higher-order beliefs…

Artificial Intelligence · Computer Science 2024-12-13 Qi Shi , Pavel Naumov

In this simple article, with possible applications in theoretical and applied physics, we suggest an original way to derive the expression of Shannon's entropy from a purely variational approach,using constraints. Based on the work of Edwin…

Statistical Mechanics · Physics 2021-07-13 Thomas Cailleteau

We study the framework of abductive logic programming extended with integrity constraints. For this framework, we introduce a new measure of the simplicity of an explanation based on its degree of \emph{arbitrariness}: the more arbitrary…

Logic in Computer Science · Computer Science 2020-02-19 Luciano Caroprese , Irina Trubitsyna , Miroslaw Truszczynski , Ester Zumpano

Complex systems are characterized by specific time-dependent interactions among their many constituents. As a consequence they often manifest rich, non-trivial and unexpected behavior. Examples arise both in the physical and non-physical…

Physics and Society · Physics 2018-11-21 Yurij Holovatch , Ralph Kenna , Stefan Thurner

The perturbation theory based on typicality introduced in Ref. [1] and further refined in Refs. [2, 3] provides a powerful tool since it is intended to be applicable to a wide range of scenarios while relying only on a few parameters. Even…

Quantum Physics · Physics 2022-12-07 Mats H. Lamann , Jochen Gemmer

In physics, there is the prevailing intuition that we are part of a unique external world, and that the goal of physics is to understand and describe this world. This assumption of the fundamentality of objective reality is often seen as a…

Quantum Physics · Physics 2019-07-22 Markus P. Mueller

In recent years extensive theoretical and experimental studies of universal few-body physics have led to advances in our understanding of universal Efimov physics [1]. The Efimov effect, once considered a mysterious and esoteric effect, is…

Quantum Gases · Physics 2015-06-03 Jia Wang , J. P. D'Incao , B. D. Esry , Chris H. Greene

We present several philosophical ideas emerging from the studies of complex systems. We make a brief introduction to the basic concepts of complex systems, for then defining "abstraction levels". These are useful for representing…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Carlos Gershenson

Preference cycles are prevalent in problems of decision-making, and are contradictory when preferences are assumed to be transitive. This contradiction underlies Condorcet's Paradox, a pioneering result of Social Choice Theory, wherein…

Algebraic Topology · Mathematics 2026-04-21 Ori Livson , Siddharth Pritam , Mikhail Prokopenko

What is the origin of macroscopic randomness (uncertainty)? This is one of the most fundamental open questions for human being. In this paper, 10000 samples of reliable (convergent), multiple-scale (from 1.0E-60 to 100) numerical…

Chaotic Dynamics · Physics 2015-09-09 Shijun Liao , Xiaoming Li

This chapter provides a overview of Bayesian inference, mostly emphasising that it is a universal method for summarising uncertainty and making estimates and predictions using probability statements conditional on observed data and an…

Methodology · Statistics 2010-02-11 Christian P. Robert , Jean-Michel Marin , Judith Rousseau

Kolmogorov complexity of a finite binary word reflects both algorithmic structure and the empirical distribution of symbols appearing in the word. Words with symbol frequencies far from one half have smaller combinatorial richness and…

Computation · Statistics 2025-12-25 Brani Vidakovic

The compactness phenomenon is one of the featured aspects of structuralism in mathematics. In simple and broad words, a compactness property holds in a structure if a related property is satisfied by sufficiently many substructures of that…

Logic · Mathematics 2024-08-29 Rahman Mohammadpour

The logic of uncertainty is not the logic of experience and as well as it is not the logic of chance. It is the logic of experience and chance. Experience and chance are two inseparable poles. These are two dual reflections of one essence,…

General Finance · Quantitative Finance 2018-10-03 Oleg Yu Vorobyev

Information theory is built on probability measures and by definition a probability measure has total mass 1. Probability measures are used to model uncertainty, and one may ask how important it is that the total mass is one. We claim that…

Information Theory · Computer Science 2022-02-08 Peter Harremoës

We recently performed cognitive experiments on conjunctions and negations of two concepts with the aim of investigating the combination problem of concepts. Our experiments confirmed the deviations (conceptual vagueness, underextension,…

Artificial Intelligence · Computer Science 2016-09-09 Diederik Aerts , Sandro Sozzo , Tomas Veloz

Contextuality is one way of capturing the non-classicality of quantum theory. The contextual nature of a theory is often witnessed via the violation of non-contextuality inequalities---certain linear inequalities involving probabilities of…

Quantum Physics · Physics 2020-07-08 Kishor Bharti , Atul Singh Arora , Leong Chuan Kwek , Jérémie Roland

The generation of comprehensible explanations is an essential feature of modern artificial intelligence systems. In this work, we consider probabilistic logic programming, an extension of logic programming which can be useful to model…

Artificial Intelligence · Computer Science 2023-08-17 Germán Vidal