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Probability theory, epistemically interpreted, provides an excellent, if not the best available account of inductive reasoning. This is so because there are general and definite rules for the change of subjective probabilities through…

Artificial Intelligence · Computer Science 2013-04-10 Wolfgang Spohn

The aim of this paper is to show that partial probability can be justified from the standpoint of subjective probability in much the same way as classical probability does. The seminal works of Ramsey and De Finetti have furnished a method…

Logic · Mathematics 2014-06-02 Maurizio Negri

Motivated by the problem of finding finite versions of classical incompleteness theorems, we present some conjectures that go beyond ${\bf NP\neq co NP}$. These conjectures formally connect computational complexity with the difficulty of…

Logic · Mathematics 2017-05-22 Pavel Pudlak

We elucidate a close connection between the Theory of Judgment Aggregation (more generally, Evaluation Aggregation), and a relatively young but rapidly growing field of universal algebra, that was primarily developed to investigate…

Computational Complexity · Computer Science 2015-06-04 Mario Szegedy , Yixin Xu

On the topic of probabilistic rewriting, there are several works studying both termination and confluence of different systems. While working with a lambda calculus modelling quantum computation, we found a system with probabilistic…

Logic in Computer Science · Computer Science 2022-04-11 Rafael Romero , Alejandro Díaz-Caro

The multiple extension problem arises frequently in diagnostic and default inference. That is, we can often use any of a number of sets of defaults or possible hypotheses to explain observations or make Predictions. In default inference,…

Artificial Intelligence · Computer Science 2013-04-11 Eric Neufeld , David L Poole

Eilenberg-type correspondences, relating varieties of languages (e.g. of finite words, infinite words, or trees) to pseudovarieties of finite algebras, form the backbone of algebraic language theory. Numerous such correspondences are known…

Formal Languages and Automata Theory · Computer Science 2017-02-27 Henning Urbat , Jiří Adámek , Liang-Ting Chen , Stefan Milius

In this paper, the feasibility of using finite totally ordered probability models under Alelinnas's Theory of Probabilistic Logic [Aleliunas, 1988] is investigated. The general form of the probability algebra of these models is derived and…

Artificial Intelligence · Computer Science 2013-04-08 Yang Xiang , Michael P. Beddoes , David L Poole

A standard Hilbert-space proof of Dirichlet's principle is simplified, using an observation that a certain form of min-problem has unique solution, at a specified point. This solves Dirichlet's problem, after it is recast in the required…

Functional Analysis · Mathematics 2010-12-24 H. N. Friedel

In this paper we discuss the consistency concept of Williams coherence for imprecise conditional previsions, presenting a variant of this notion, which we call W-coherence. It is shown that W-coherence ensures important consistency…

Probability · Mathematics 2015-03-10 Renato Pelessoni , Paolo Vicig

Recently, there has been some discussion of how Dutch Book arguments might be used to demonstrate the rational incoherence of certain hidden variable models of quantum theory (Feintzeig and Fletcher 2017). In this paper, we argue that the…

Quantum Physics · Physics 2018-09-12 Jeremy Steeger , Nicholas Teh

Randomization tests are based on a re-randomization of existing data to gain data-dependent critical values that lead to exact hypothesis tests under special circumstances. However, it is not always possible to re-randomize data in…

Statistics Theory · Mathematics 2021-10-20 Dennis Dobler

Epistemic uncertainty arises in lack of complete knowledge about the state of a system. There are multiple mathematical frameworks for measuring such uncertainty quantitatively, often referred to as imprecise probability theories. Inspired…

Category Theory · Mathematics 2026-03-05 Torgeir Aambø

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

We study the binary Ehrenfeucht Mycielski sequence seeking a balance between the number of occurrences of different binary strings. There have been numerous attempts to prove the balance conjecture of the sequence, which roughly states that…

Discrete Mathematics · Computer Science 2017-10-05 Kundan Krishna , Satyadev Nandakumar

Rule based classifiers that use the presence and absence of key sub-strings to make classification decisions have a natural mechanism for quantifying the uncertainty of their precision. For a binary classifier, the key insight is to treat…

Machine Learning · Computer Science 2020-05-20 James Nutaro , Ozgur Ozmen

Integral operators of Abel type of order a > 0 arise naturally in a large spectrum of physical processes. Their inversion requires care since the resulting inverse problem is ill-posed. The purpose of this work is to devise and analyse a…

Functional Analysis · Mathematics 2021-07-27 Cecile Della Valle , Camille Pouchol

We study formal languages which are capable of fully expressing quantitative probabilistic reasoning and do-calculus reasoning for causal effects, from a computational complexity perspective. We focus on satisfiability problems whose…

Artificial Intelligence · Computer Science 2023-05-17 Benito van der Zander , Markus Bläser , Maciej Liśkiewicz

The aim of the paper is to derive essential elements of quantum mechanics from a parametric structure extending that of traditional mathematical statistics. The main extensions, which also can be motivated from an applied statistics point…

Quantum Physics · Physics 2012-07-10 Inge S. Helland

In this paper, we consider the coherent theory of (epistemic) uncertainty of Walley, in which beliefs are represented through sets of probability distributions, and we focus on the problem of modeling prior ignorance about a categorical…

Machine Learning · Computer Science 2014-07-15 Alberto Piatti , Marco Zaffalon , Fabio Trojani , Marcus Hutter