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We present a computational model of mathematical reasoning according to which mathematics is a fundamentally stochastic process. That is, on our model, whether or not a given formula is deemed a theorem in some axiomatic system is not a…

Logic · Mathematics 2020-12-16 David H. Wolpert , David Kinney

Abstract argumentation offers an appealing way of representing and evaluating arguments and counterarguments. This approach can be enhanced by a probability assignment to each argument. There are various interpretations that can be ascribed…

Artificial Intelligence · Computer Science 2014-05-15 Anthony Hunter , Matthias Thimm

We explore the notion of uncertainty in the context of modern abstractive summarization models, using the tools of Bayesian Deep Learning. Our approach approximates Bayesian inference by first extending state-of-the-art summarization models…

Computation and Language · Computer Science 2022-05-04 Alexios Gidiotis , Grigorios Tsoumakas

The notion of argumentation and the one of belief stand in a problematic relation to one another. On the one hand, argumentation is crucial for belief formation: as the outcome of a process of arguing, an agent might come to (justifiably)…

Logic in Computer Science · Computer Science 2021-06-23 Alfredo Burrieza , Antonio Yuste-Ginel

Modern scientific cosmology pushes the boundaries of knowledge and the knowable. This is prompting questions on the nature of scientific knowledge. A central issue is what defines a 'good' model. When addressing global properties of the…

History and Philosophy of Physics · Physics 2018-12-12 Martin Sahlén

You and I are highly unlikely to exist in a civilization that has produced only 70 billion people, yet we find ourselves in just such a civilization. Our circumstance, which seems difficult to explain, is easily accounted for if (1) many…

Popular Physics · Physics 2012-09-28 Austin Gerig

Applying automated reasoning tools for decision support and analysis in law has the potential to make court decisions more transparent and objective. Since there is often uncertainty about the accuracy and relevance of evidence,…

Artificial Intelligence · Computer Science 2020-09-15 Inga Ibs , Nico Potyka

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

Uncertainty enters into human reasoning and inference in at least two ways. It is reasonable to suppose that there will be roles for these distinct uses of uncertainty also in automated reasoning.

Artificial Intelligence · Computer Science 2013-04-10 Henry E. Kyburg

Selection effects in cosmology are often invoked to "explain" why some of the fundamental constant of Nature, and in particular the cosmological constant, take on the value they do in our Universe. We briefly review this probabilistic…

Astrophysics · Physics 2009-11-11 Roberto Trotta , Glenn D. Starkman

Whether the fate of our species can be forecast from its past has been the topic of considerable controversy. One refutation of the so-called Doomsday Argument is based on the premise that we are more likely to exist in a universe…

Other Statistics · Statistics 2016-11-10 Fergus Simpson

We revisit anthropic arguments purporting to explain the measured value of the cosmological constant. We argue that different ways of assigning probabilities to candidate universes lead to totally different anthropic predictions. As an…

Astrophysics · Physics 2007-07-23 Glenn D. Starkman , Roberto Trotta

Reasoning with defeasible and conflicting knowledge in an argumentative form is a key research field in computational argumentation. Reasoning under various forms of uncertainty is both a key feature and a challenging barrier for automated…

Artificial Intelligence · Computer Science 2024-07-09 Andrei Popescu , Johannes P. Wallner

Unaided human decision making appears to systematically violate consistency constraints imposed by normative theories; these biases in turn appear to justify the application of formal decision-analytic models. It is argued that both claims…

Artificial Intelligence · Computer Science 2013-04-08 Marvin S. Cohen

Triggered by a recent interesting New Scientist article on the too frequent incorrect use of probabilistic evidence in courts, I introduce the basic concepts of probabilistic inference with a toy model, and discuss several important issues…

History and Overview · Mathematics 2010-09-30 G. D'Agostini

We explore Bayesian reasoning as a means to quantify uncertainty in neural networks for question answering. Starting with a multilayer perceptron on the Iris dataset, we show how posterior inference conveys confidence in predictions. We…

Computation and Language · Computer Science 2025-12-22 Riccardo Di Sipio

Bayesian probability theory is used as a framework to develop a formalism for the scientific method based on principles of inductive reasoning. The formalism allows for precise definitions of the key concepts in theories of physics and also…

Data Analysis, Statistics and Probability · Physics 2011-09-12 Roberto C. Alamino

A series of monte carlo studies were performed to compare the behavior of some alternative procedures for reasoning under uncertainty. The behavior of several Bayesian, linear model and default reasoning procedures were examined in the…

Artificial Intelligence · Computer Science 2013-03-26 Paul E. Lehner , Azar Sadigh

The process of doing Science in condition of uncertainty is illustrated with a toy experiment in which the inferential and the forecasting aspects are both present. The fundamental aspects of probabilistic reasoning, also relevant in real…

History and Overview · Mathematics 2018-02-07 Giulio D'Agostini

Even when completely and consistently formulated, a fundamental theory of physics and cosmological boundary conditions may not give unambiguous and unique predictions for the universe we observe; indeed inflation, string/M theory, and…

High Energy Physics - Theory · Physics 2009-10-07 Anthony Aguirre , Max Tegmark