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Related papers: A global accuracy characterisation of trust

200 papers

Consider the following belief change/merging scenario. A group of information sources gives a sequence of reports about the state of the world at various instances (e.g. different points in time). The true states at these instances are…

Artificial Intelligence · Computer Science 2022-05-03 Joseph Singleton , Richard Booth

Trust calibration is necessary to ensure appropriate user acceptance in advanced automation technologies. A significant challenge to achieve trust calibration is to quantitatively estimate human trust in real-time. Although multiple trust…

Human-Computer Interaction · Computer Science 2023-04-17 Jundi Liu , Kumar Akash , Teruhisa Misu , Xingwei Wu

In real world complex networks, the importance of a node depends on two important parameters: 1. characteristics of the node, and 2. the context of the given application. The current literature contains several centrality measures that have…

Social and Information Networks · Computer Science 2017-11-01 Akrati Saxena , S. R. S. Iyengar

Factual consistency is one of important summary evaluation dimensions, especially as summary generation becomes more fluent and coherent. The ESTIME measure, recently proposed specifically for factual consistency, achieves high correlations…

Computation and Language · Computer Science 2022-01-10 Oleg Vasilyev , John Bohannon

We show that the deformation theory of a perfect complex and that of its determinant are related by the trace map, in a general setting of sheaves on a site. The key technical step, in passing from the setting of modules over a ring where…

Algebraic Geometry · Mathematics 2023-03-15 Max Lieblich , Martin Olsson

One problem to solve in the context of information fusion, decision-making, and other artificial intelligence challenges is to compute justified beliefs based on evidence. In real-life examples, this evidence may be inconsistent,…

Artificial Intelligence · Computer Science 2023-06-07 Daira Pinto Prieto , Ronald de Haan , Aybüke Özgün

We give a principled method for decomposing the predictive uncertainty of a model into aleatoric and epistemic components with explicit semantics relating them to the real-world data distribution. While many works in the literature have…

Machine Learning · Computer Science 2024-12-30 Gustaf Ahdritz , Aravind Gollakota , Parikshit Gopalan , Charlotte Peale , Udi Wieder

As artificial agents become increasingly capable, what internal structure is *necessary* for an agent to act competently under uncertainty? Classical results show that optimal control can be *implemented* using belief states or world…

Machine Learning · Computer Science 2026-04-03 Aran Nayebi

In the Hegselmann-Krause model, an agent updates its opinion by averaging with others whose opinions differ by at most a given confidence threshold. With agents' initial opinions uniformly distributed on the unit interval, we provide a…

Probability · Mathematics 2024-08-08 Hsin-Lun Li

Coherence is a defining property of quantum theory that accounts for quantum advantage in many quantum information tasks. Although many coherence quantifiers have been introduced in various contexts, the lack of efficient methods to…

Quantum Physics · Physics 2023-01-02 Sun Liang Liang , Yu Sixia

The principle that rational agents should maximize expected utility or choiceworthiness is intuitively plausible in many ordinary cases of decision-making under uncertainty. But it is less plausible in cases of extreme, low-probability risk…

Theoretical Economics · Economics 2020-08-11 Christian Tarsney

We introduce the notion of an approximation system as a generalization of Taylor approximation, and we give some first examples. Next we develop the general theory, including error bounds and a sufficient criterion for convergence. More…

Classical Analysis and ODEs · Mathematics 2017-10-20 Victor A. Pessers , Tom H. Koornwinder

Bayesian inference requires specification of a single, precise prior distribution, whereas frequentist inference only accommodates a vacuous prior. Since virtually every real-world application falls somewhere in between these two extremes,…

Methodology · Statistics 2023-09-26 Ryan Martin

In this paper, we propose and analyze a trust-region model-based algorithm for solving unconstrained stochastic optimization problems. Our framework utilizes random models of an objective function $f(x)$, obtained from stochastic…

Optimization and Control · Mathematics 2016-09-26 Ruobing Chen , Matt Menickelly , Katya Scheinberg

In this work, we aim to create a completely online algorithmic framework for prediction with expert advice that is translation-free and scale-free of the expert losses. Our goal is to create a generalized algorithm that is suitable for use…

Machine Learning · Computer Science 2020-09-10 Kaan Gokcesu , Hakan Gokcesu

Dempster/Shafer (D/S) theory has been advocated as a way of representing incompleteness of evidence in a system's knowledge base. Methods now exist for propagating beliefs through chains of inference. This paper discusses how rules with…

Artificial Intelligence · Computer Science 2013-04-10 Paul K. Black , Kathryn Blackmond Laskey

Trustworthiness and trust are basic factors in common societies that allow us to interact and enjoy being in crowds without fear. As robotic devices start percolating into our daily lives they must behave as fully trustworthy objects, such…

Computers and Society · Computer Science 2025-04-15 Gerhard P. Fettweis , Patricia Grünberg , Tim Hentschel , Stefan Köpsell

Complex decision-making systems rarely have direct access to the current state of the world and they instead rely on opinions to form an understanding of what the ground truth could be. Even in problems where experts provide opinions…

Artificial Intelligence · Computer Science 2023-08-22 Noyan C. Sevuktekin , Andrew C. Singer

We consider the relation between knowledge and certainty, where a fact is known if it is true at all worlds an agent considers possible and is certain if it holds with probability 1. We identify certainty with probabilistic belief. We show…

Artificial Intelligence · Computer Science 2013-04-08 Joseph Y. Halpern

Whereas deterministic protocols are typically guaranteed to obtain particular goals of interest, probabilistic protocols typically provide only probabilistic guarantees. This paper initiates an investigation of the interdependence between…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-07-08 Nitzan Zamir , Yoram Moses