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Related papers: (Non-)Commutative Aggregation

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Aggregating conformal predictors is a standard way of balancing their predictive and computational efficiency while retaining their validity, at least approximately. An important advantage of conformal e-predictors is that they are easier…

Machine Learning · Computer Science 2026-05-11 Vladimir Vovk

Prior proposals for cumulative statistics suggest making tiny random perturbations to the scores (independent variables in a regression) in order to ensure the scores' uniqueness. Uniqueness means that no score for any member of the…

Methodology · Statistics 2022-08-23 Mark Tygert

Explaining why aggregated measures change is a critical challenge in data analytics that existing systems struggle to address. While current attribution methods exist, they lack a unified solution that is simultaneously general for…

Information Retrieval · Computer Science 2026-04-30 Changsheng Zhou , Dajun Chen , Zhitao Shen , wei jiang , Yong Li , Peng Di

Completeness and transitivity are standard rationality conditions in economics. However, under ambiguity, decision makers sometimes violate these requirements because of the difficulty of forming accurate predictions about ambiguous events.…

Theoretical Economics · Economics 2025-09-16 Kensei Nakamura , Shohei Yanagita

Standard models of multi-agent modal logic do not capture the fact that information is often ambiguous, and may be interpreted in different ways by different agents. We propose a framework that can model this, and consider different…

Artificial Intelligence · Computer Science 2012-03-06 Joseph Y. Halpern , Willemien Kets

This paper studies manipulation of belief aggregation rules in the setting where the society first collects individual's probabilistic opinions and then solves a public portfolio choice problem with common utility based on the aggregate…

Theoretical Economics · Economics 2024-05-06 Christopher P. Chambers , Federico Echenique , Takashi Hayashi

This note is concerned with a formal analysis of the problem of non-monotonic reasoning in intelligent systems, especially when the uncertainty is taken into account in a quantitative way. A firm connection between logic and probability is…

Artificial Intelligence · Computer Science 2013-04-05 Hung-Trung Nguyen

We propose a decision-analytical approach to comparing the flexibility of decision situations from the perspective of a decision-maker who exhibits constant risk-aversion over a monetary value model. Our approach is simple yet seems to be…

Artificial Intelligence · Computer Science 2013-02-18 Ross D. Shachter , Marvin Mandelbaum

We introduce a number of logics to reason about collective propositional attitudes that are defined by means of the majority rule. It is well known that majoritarian aggregation is subject to irrationality, as the results in social choice…

Logic in Computer Science · Computer Science 2017-11-13 Daniele Porello

The literature on judgment aggregation is moving from studying impossibility results regarding aggregation rules towards studying specific judgment aggregation rules. Here we give a structured list of most rules that have been proposed and…

Artificial Intelligence · Computer Science 2016-12-07 Jerôme Lang , Gabriella Pigozzi , Marija Slavkovik , Leendert van der Torre , Srdjan Vesic

We study belief revision when information is represented by a set of probability distributions, or general information. General information extends the standard event notion while including qualitative information (A is more likely than B),…

Theoretical Economics · Economics 2025-02-04 Adam Dominiak , Matthew Kovach , Gerelt Tserenjigmid

Probabilistic game structures combine both nondeterminism and stochasticity, where players repeatedly take actions simultaneously to move to the next state of the concurrent game. Probabilistic alternating simulation is an important tool to…

Logic in Computer Science · Computer Science 2019-07-10 Chenyi Zhang , Jun Pang

This paper studies preference aggregation under ambiguity when agents have incomplete preference relations due to imprecise beliefs. We introduce the "dual" of the Pareto principle, which respects unanimity among individuals, including…

Theoretical Economics · Economics 2025-12-19 Leo Kurata , Kensei Nakamura

This paper introduces a qualitative measure of ambiguity and analyses its relationship with other measures of uncertainty. Probability measures relative likelihoods, while ambiguity measures vagueness surrounding those judgments. Ambiguity…

Artificial Intelligence · Computer Science 2013-03-08 Michael S. K. M. Wong , Z. W. Wang

We consider a voting model, where a number of candidates need to be selected subject to certain feasibility constraints. The model generalises committee elections (where there is a single constraint on the number of candidates that need to…

Computer Science and Game Theory · Computer Science 2025-09-24 Tomáš Masařík , Grzegorz Pierczyński , Piotr Skowron

The paper studies the notion of supposition encoded in non-Archimedean conditional probability (and revealed in the acceptance of the so-called indicative conditionals). The notion of qualitative change of view that thus arises is…

Artificial Intelligence · Computer Science 2007-05-23 Horacio Arlo-Costa

Contextuality is usually defined as absence of a joint distribution for a set of measurements (random variables) with known joint distributions of some of its subsets. However, if these subsets of measurements are not disjoint,…

Quantum Physics · Physics 2017-09-05 Ehtibar Dzhafarov , Janne Kujala

Judgment aggregation problems form a class of collective decision-making problems represented in an abstract way, subsuming some well known problems such as voting. A collective decision can be reached in many ways, but a direct one-step…

Artificial Intelligence · Computer Science 2016-08-30 Marija Slavkovik , Wojciech Jamroga

We present a general logical framework for reasoning about agents' cognitive attitudes of both epistemic type and motivational type. We show that it allows us to express a variety of relevant concepts for qualitative decision theory…

Artificial Intelligence · Computer Science 2023-06-22 Emiliano Lorini

We revisit and generalize the concept of composite likelihood as a method to make a probabilistic inference by aggregation of multiple Bayesian agents, thereby defining a class of predictive models which we call composite Bayesian. This…

Computation · Statistics 2019-04-18 Alexis Roche