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The Shapley value, originating from cooperative game theory, has been employed to define responsibility measures that quantify the contributions of database facts to obtaining a given query answer. For non-numeric queries, this is done by…

Databases · Computer Science 2026-01-19 Meghyn Bienvenu , Diego Figueira , Pierre Lafourcade

Following the work of Lloyd Shapley on the Shapley value, and tangentially the work of Guillermo Owen, we offer an alternative non-probabilistic formulation of part of the work of Robert J. Weber in his 1978 paper "Probabilistic values for…

Theoretical Economics · Economics 2019-05-13 Jacob North Clark , Stephen Montgomery-Smith

Multiwinner voting rules are used to select a small representative subset of candidates or items from a larger set given the preferences of voters. However, if candidates have sensitive attributes such as gender or ethnicity (when selecting…

Computers and Society · Computer Science 2018-06-20 L. Elisa Celis , Lingxiao Huang , Nisheeth K. Vishnoi

We provide a formal definition of blameworthiness in settings where multiple agents can collaborate to avoid a negative outcome. We first provide a method for ascribing blameworthiness to groups relative to an epistemic state (a…

Computers and Society · Computer Science 2019-03-12 Meir Friedenberg , Joseph Y. Halpern

Two straightforward methods to extend an assessment of individual elements to groups are to sum individual assessments or to treat the group as a single merged element and assess it accordingly. In this work, we analyze another natural…

Computer Science and Game Theory · Computer Science 2026-05-21 Piotr Kępczyński , Oskar Skibski

We investigate the distribution of the well-studied Shapley--Shubik values in weighted voting games where the agents are stochastically determined. The Shapley--Shubik value measures the voting power of an agent, in typical collective…

Computer Science and Game Theory · Computer Science 2016-01-26 Yuval Filmus , Joel Oren , Kannan Soundararajan

Multi-winner voting is the process of selecting a fixed-size set of representative candidates based on voters' preferences. It occurs in applications ranging from politics (parliamentary elections) to the design of modern computer…

Computer Science and Game Theory · Computer Science 2022-11-22 Martin Lackner , Piotr Skowron

Traditionally social sciences are interested in structuring people in multiple groups based on their individual preferences. This pa- per suggests an approach to this problem in the framework of a non- cooperative game theory. Definition of…

Optimization and Control · Mathematics 2017-05-02 Dmitry Levando

Blame attribution is one of the key aspects of accountable decision making, as it provides means to quantify the responsibility of an agent for a decision making outcome. In this paper, we study blame attribution in the context of…

Artificial Intelligence · Computer Science 2022-01-26 Stelios Triantafyllou , Adish Singla , Goran Radanovic

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

Measuring contributions is a classical problem in cooperative game theory where the Shapley value is the most well-known solution concept. In this paper, we establish the convergence property of the Shapley value in parametric Bayesian…

Machine Learning · Computer Science 2022-06-15 Lucas Agussurja , Xinyi Xu , Bryan Kian Hsiang Low

Feature selection is a classical problem in statistics and machine learning, and it continues to remain an extremely challenging problem especially in the context of unknown non-linear relationships with dependent features. On the other…

Machine Learning · Statistics 2026-04-17 Chenghui Zheng , Garvesh Raskutti

Collaborative machine learning (ML) is an appealing paradigm to build high-quality ML models by training on the aggregated data from many parties. However, these parties are only willing to share their data when given enough incentives,…

Machine Learning · Computer Science 2020-10-27 Rachael Hwee Ling Sim , Yehong Zhang , Mun Choon Chan , Bryan Kian Hsiang Low

Committee scoring rules form a rich class of aggregators of voters' preferences for the purpose of selecting subsets of objects with desired properties, e.g., a shortlist of candidates for an interview, a representative collective body such…

Computer Science and Game Theory · Computer Science 2016-11-03 Piotr Skowron , Piotr Faliszewski , Arkadii Slinko

Not all real-world data are labeled, and when labels are not available, it is often costly to obtain them. Moreover, as many algorithms suffer from the curse of dimensionality, reducing the features in the data to a smaller set is often of…

Machine Learning · Computer Science 2022-05-19 Chiara Balestra , Florian Huber , Andreas Mayr , Emmanuel Müller

Measuring individual productivity (or equivalently distributing the overall productivity) in a network structure of workers displaying peer effects has been a subject of ongoing interest in many areas ranging from academia to industry. In…

Computer Science and Game Theory · Computer Science 2024-02-07 N. Allouch , Luis A. Guardiola , A. Meca

We design two mechanisms that ensure that the majority preferred option wins in all equilibria. The first one is a simultaneous game where agents choose other agents to cooperate with on top of the vote for an alternative, thus overcoming…

Theoretical Economics · Economics 2023-10-12 Kirneva Margarita , Núñez Matías

We introduce a natural variant of weighted voting games, which we refer to as k-Prize Weighted Voting Games. Such games consist of n players with weights, and k prizes, of possibly differing values. The players form coalitions, and the i-th…

Computer Science and Game Theory · Computer Science 2023-03-03 Wei-Chen Lee , David Hyland , Alessandro Abate , Edith Elkind , Jiarui Gan , Julian Gutierrez , Paul Harrenstein , Michael Wooldridge

Originally introduced in cooperative game theory, Shapley values have become a very popular tool to explain machine learning predictions. Based on Shapley's fairness axioms, every input (feature component) gets a credit how it contributes…

Machine Learning · Statistics 2025-08-19 Michael Mayer , Mario V. Wüthrich

We consider a committee voting on whether to adopt a reform under a quota rule, where members differ in how much they value the reform some supporting it, others opposing it. We examine how members can influence each other's votes through…

General Economics · Economics 2025-05-19 Ali Lazrak , Jianfeng Zhang
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