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Related papers: A behavioral interpretation of belief functions

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The general use of subjective probabilities to model belief has been justified using many axiomatic schemes. For example, ?consistent betting behavior' arguments are well-known. To those not already convinced of the unique fitness and…

Artificial Intelligence · Computer Science 2013-03-25 Paul Snow

Reacting against the limitation of statistics to decision procedures, R. A. Fisher proposed for inductive reasoning the use of the fiducial distribution, a parameter-space distribution of epistemological probability transferred directly…

Statistics Theory · Mathematics 2013-03-01 David R. Bickel

A large branch of explainable machine learning is grounded in cooperative game theory. However, research indicates that game-theoretic explanations may mislead or be hard to interpret. We argue that often there is a critical mismatch…

Machine Learning · Computer Science 2024-10-28 Luca Franceschi , Michele Donini , Cédric Archambeau , Matthias Seeger

Inappropriate use of Dempster's rule of combination has led some authors to reject the Dempster-Shafer model, arguing that it leads to supposedly unacceptable conclusions when defaults are involved. A most classic example is about the…

Artificial Intelligence · Computer Science 2013-04-05 Philippe Smets , Yen-Teh Hsia

This paper suggests a new interpretation of the Dempster-Shafer theory in terms of probabilistic interpretation of plausibility. A new rule of combination of independent evidence is shown and its preservation of interpretation is…

Artificial Intelligence · Computer Science 2017-04-07 Mieczysław Kłopotek

In this paper, we describe a scheme for propagating belief functions in certain kinds of trees using only local computations. This scheme generalizes the computational scheme proposed by Shafer and Logan1 for diagnostic trees of the type…

Artificial Intelligence · Computer Science 2013-04-12 Prakash P. Shenoy , Glenn Shafer , Khaled Mellouli

The notion of belief likelihood function of repeated trials is introduced, whenever the uncertainty for individual trials is encoded by a belief measure (a finite random set). This generalises the traditional likelihood function, and…

Statistics Theory · Mathematics 2018-08-21 Fabio Cuzzolin

To model discrete-time finite-state uncertain processes, we argue for the use of a global belief model in the form of an upper expectation that is the most conservative one under a set of basic axioms. Our motivation for these axioms, which…

Probability · Mathematics 2021-01-12 Natan T'Joens , Jasper De Bock , Gert de Cooman

A key feature of human theory-of-mind is the ability to attribute beliefs to other agents as mentalistic explanations for their behavior. But given the wide variety of beliefs that agents may hold about the world and the rich language we…

Computation and Language · Computer Science 2025-05-27 Lance Ying , Almog Hillel , Ryan Truong , Vikash K. Mansinghka , Joshua B. Tenenbaum , Tan Zhi-Xuan

The problem of combining beliefs in the Dempster-Shafer belief theory has attracted considerable attention over the last two decades. The classical Dempster's Rule has often been criticised, and many alternative rules for belief combination…

Artificial Intelligence · Computer Science 2007-05-23 Audun Josang

Accepting a proposition means that our confidence in this proposition is strictly greater than the confidence in its negation. This paper investigates the subclass of uncertainty measures, expressing confidence, that capture the idea of…

Artificial Intelligence · Computer Science 2013-02-21 Didier Dubois , Henri Prade

The advent and proliferation of social media have led to the development of mathematical models describing the evolution of beliefs/opinions in an ecosystem composed of socially interacting users. The goal is to gain insights into…

Social and Information Networks · Computer Science 2017-10-04 Alessandro Nordio , Alberto Tarable , Carla Fabiana Chiasserini , Emilio Leonardi

Many models of economics assume that individuals distort objective probabilities. We propose a simple consistency condition on distortion functions, which we term distortion coherence, that ensures that the function commutes with…

Theoretical Economics · Economics 2024-06-10 Christopher P. Chambers , Yusufcan Masatlioglu , Collin Raymond

Note: Published now as a chapter in "Handbook of the History and Philosophy of Mathematical Practice" (Springer Nature, editor B. Sriraman, https://doi.org/10.1007/978-3-030-19071-2_105-1). The application of mathematical probability theory…

Other Statistics · Statistics 2023-11-21 Christian Hennig

It has been shown that a functional interpretation of proofs in mathematical analysis can be given by the product of selection functions, a mode of recursion that has an intuitive reading in terms of the computation of optimal strategies in…

Logic · Mathematics 2012-04-25 Paulo Oliva , Thomas Powell

The Dempster--Shafer (DS) theory is a powerful tool for probabilistic reasoning based on a formal calculus for combining evidence. DS theory has been widely used in computer science and engineering applications, but has yet to reach the…

Methodology · Statistics 2010-11-04 Ryan Martin , Jianchun Zhang , Chuanhai Liu

Variational inference algorithms such as belief propagation have had tremendous impact on our ability to learn and use graphical models, and give many insights for developing or understanding exact and approximate inference. However,…

Artificial Intelligence · Computer Science 2012-10-19 Qiang Liu , Alexander T. Ihler

Belief systems are often treated as globally consistent sets of propositions or as scalar-valued probability distributions. Such representations tend to obscure the internal structure of belief, conflate external credibility with internal…

Artificial Intelligence · Computer Science 2025-08-06 Saleh Nikooroo

Agents often have individual goals which depend on a group's actions. If agents trust a forecast of collective action and adapt strategically, such prediction can influence outcomes non-trivially, resulting in a form of performative…

Machine Learning · Computer Science 2025-02-18 António Góis , Mehrnaz Mofakhami , Fernando P. Santos , Gauthier Gidel , Simon Lacoste-Julien

The main goal of this paper is to describe an axiomatic utility theory for Dempster-Shafer belief function lotteries. The axiomatic framework used is analogous to von Neumann-Morgenstern's utility theory for probabilistic lotteries as…

Artificial Intelligence · Computer Science 2020-07-16 Thierry Denoeux , Prakash P. Shenoy