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We study a portioning setting in which a public resource such as time or money is to be divided among a given set of candidates, and each agent proposes a division of the resource. We consider two families of aggregation rules for this…

Computer Science and Game Theory · Computer Science 2026-01-27 Edith Elkind , Matthias Greger , Patrick Lederer , Warut Suksompong , Nicholas Teh

Data based judgments go into artificial intelligence applications but they undergo paradoxical reversal when seemingly unnecessary additional data is provided. Examples of this are Simpson's reversal and the disjunction effect where the…

Artificial Intelligence · Computer Science 2017-09-14 Subhash Kak

In this paper we propose a new family of Belief Conditioning Rules (BCRs) for belief revision. These rules are not directly related with the fusion of several sources of evidence but with the revision of a belief assignment available at a…

Artificial Intelligence · Computer Science 2007-05-23 Florentin Smarandache , Jean Dezert

We study combinations of risk measures under no restrictive assumption on the set of alternatives. We develop and discuss results regarding the preservation of properties and acceptance sets for the combinations of risk measures. One of the…

Mathematical Finance · Quantitative Finance 2023-05-09 Marcelo Brutti Righi

When we merge information in Dempster-Shafer Theory (DST), we are faced with anomalous behavior: agents with equal expertise and credibility can have their opinion disregarded after resorting to the belief combination rule of this theory.…

Artificial Intelligence · Computer Science 2024-08-20 Francisco Aragão , João Alcântara

We introduce a general theory of epistemic random fuzzy sets for reasoning with fuzzy or crisp evidence. This framework generalizes both the Dempster-Shafer theory of belief functions, and possibility theory. Independent epistemic random…

Artificial Intelligence · Computer Science 2024-05-08 Thierry Denoeux

Belief function theory provides a flexible way to combine information provided by different sources. This combination is usually followed by a decision making which can be handled by a range of decision rules. Some rules help to choose the…

Artificial Intelligence · Computer Science 2015-01-29 Amira Essaid , Arnaud Martin , Grégory Smits , Boutheina Ben Yaghlane

Modifiable combining functions are a synthesis of two common approaches to combining evidence. They offer many of the advantages of these approaches and avoid some disadvantages. Because they facilitate the acquisition, representation,…

Artificial Intelligence · Computer Science 2013-04-11 Paul Cohen , Glenn Shafer , Prakash P. Shenoy

Many problems in Physics and Chemistry are formulated as the minimization of a functional. Therefore, methods for solving these problems typically require differentiating maps whose input and/or output are functions -- commonly referred to…

Mathematical Software · Computer Science 2024-06-25 Kangbo Li , Anil Damle

We first show that there are practical situations in for instance forensic and gambling settings, in which applying classical probability theory, that is, based on the axioms of Kolmogorov, is problematic. We then introduce and discuss…

Probability · Mathematics 2015-12-07 Timber Kerkvliet , Ronald Meester

This paper presents a general method for combining uncertain and paradoxical source of evidences for a wide class of fusion problems. From the foundations of the Dezert-Smarandache Theory (DSmT) we show how the DSm rule of combination can…

Dynamical Systems · Mathematics 2007-05-23 Jean Dezert , Florentin Smarandache

A semantics is given to possibilistic logic, a logic that handles weighted classical logic formulae, and where weights are interpreted as lower bounds on degrees of certainty or possibility, in the sense of Zadeh's possibility theory. The…

Artificial Intelligence · Computer Science 2013-03-26 Jerome Lang , Didier Dubois , Henri Prade

This paper is aimed at providing a uniform framework for reasoning about beliefs of multiple agents and their fusion. In the first part of the paper, we develop logics for reasoning about cautiously merged beliefs of agents with different…

Artificial Intelligence · Computer Science 2007-05-23 Churn-Jung Liau

This paper discusses how a measure of uncertainty representing a state of knowledge can be updated when a new information, which may be pervaded with uncertainty, becomes available. This problem is considered in various framework, namely:…

Artificial Intelligence · Computer Science 2013-04-05 Didier Dubois , Henri Prade

Several rules for social choice are examined from a unifying point of view that looks at them as procedures for revising a system of degrees of belief in accordance with certain specified logical constraints. Belief is here a social…

Artificial Intelligence · Computer Science 2015-05-06 Rosa Camps , Xavier Mora , Laia Saumell

In this contribution we explore choice revision, a sort of belief change in which the new information is represented by a set of sentences and the agent could accept some of the sentences while rejecting the others. We propose a generalized…

Logic in Computer Science · Computer Science 2018-05-04 Li Zhang

This short technical note points out an erroneous claim about a new rule of combination of basic belief assignments presented recently by Kenn et al. in 2023, referred as Kenn's rule of combination (or just as KRC for short). We prove…

Artificial Intelligence · Computer Science 2023-03-07 Jean Dezert , Albena Tchamova

We establish a link between multiwinner elections and apportionment problems by showing how approval-based multiwinner election rules can be interpreted as methods of apportionment. We consider several multiwinner rules and observe that…

Computer Science and Game Theory · Computer Science 2021-04-21 Markus Brill , Jean-François Laslier , Piotr Skowron

The ethic of proportional redistribution is a compromise between the extremely compensatory ethic of full redistribution and the needs-blind ethic of laissez-faire. In a basic model of redistribution problems with needs, we characterize…

Theoretical Economics · Economics 2025-12-01 Ricardo Martinez , Juan D. Moreno-Ternero

This paper will focus on the process of 'fusing' several observations or models of uncertainty into a single resultant model. Many existing approaches to fusion use subjective quantities such as 'strengths of belief' and process these…

Artificial Intelligence · Computer Science 2020-07-28 Shawn C. Eastwood , Svetlana N. Yanushkevich