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We extend Approval voting to the settings where voters may have intransitive preferences. The major obstacle to applying Approval voting in these settings is that voters are not able to clearly determine who they should approve or…

Computer Science and Game Theory · Computer Science 2017-02-28 Yongjie Yang

One of the benefits of belief networks and influence diagrams is that so much knowledge is captured in the graphical structure. In particular, statements of conditional irrelevance (or independence) can be verified in time linear in the…

Artificial Intelligence · Computer Science 2013-02-01 Ross D. Shachter

May's Theorem [K. O. May, Econometrica 20 (1952) 680-684] characterizes majority voting on two alternatives as the unique preferential voting method satisfying several simple axioms. Here we show that by adding some desirable axioms to…

Theoretical Economics · Economics 2025-04-29 Wesley H. Holliday , Eric Pacuit

Dropout is attracting intensive research interest in deep learning as an efficient approach to prevent overfitting. Recently incorporating structural information when deciding which units to drop out produced promising results comparing to…

Machine Learning · Computer Science 2021-06-17 Xiaoli Li

This paper considers the ranking problem of candidates for a certain position based on ballot papers filled by voters. We suggest a ranking procedure of alternatives using cooperative game theory methods. For this, it is necessary to…

Computer Science and Game Theory · Computer Science 2022-09-09 Aleksei Kondratev , Vladimir Mazalov

In an election in which each voter ranks all of the candidates, we consider the head-to-head results between each pair of candidates and form a labeled directed graph, called the margin graph, which contains the margin of victory of each…

Theoretical Economics · Economics 2020-09-08 Matthew Harrison-Trainor

Voting Advice Applications (VAA) are tools designed to help voters compare political candidates on policy preferences prior to elections. VAAs are popular tools in European countries and in other countries with multi-party democratic…

Computers and Society · Computer Science 2026-03-05 Giovanni Astante , Roberta Sinatra , Vedran Sekara

We prove that there is no preferential voting method satisfying the Condorcet winner and loser criteria, positive involvement (if a candidate $x$ wins in an initial preference profile, then adding a voter who ranks $x$ uniquely first cannot…

Theoretical Economics · Economics 2026-02-20 Wesley H. Holliday

In this paper, we argue for a paradigm shift from the current model of explainable artificial intelligence (XAI), which may be counter-productive to better human decision making. In early decision support systems, we assumed that we could…

Artificial Intelligence · Computer Science 2023-03-14 Tim Miller

An outlier is a datapoint that is set apart from a sample population. The outlier theorem in algorithmic information theory states that given a computable sampling method, outliers must appear. We present a simple proof to the outlier…

Computational Complexity · Computer Science 2023-06-27 Samuel Epstein

Elections where electors rank the candidates (or a subset of the candidates) in order of preference allow the collection of more information about the electors' intent. The most widely used election of this type is Instant-Runoff Voting…

Computers and Society · Computer Science 2023-12-06 Michelle Blom , Peter J. Stuckey , Vanessa Teague , Damjan Vukcevic

While the number and variety of models to explain opinion exchange dynamics is huge, attempts to justify the model results using empirical data are relatively rare. As linking to real data is essential for establishing model credibility,…

Physics and Society · Physics 2015-05-18 Sven Banisch , Tanya Araújo

Lu and Boutilier proposed a novel approach based on "minimax regret" to use classical score based voting rules in the setting where preferences can be any partial (instead of complete) orders over the set of alternatives. We show here that…

Multiagent Systems · Computer Science 2017-11-13 Palash Dey

Fairness in multiwinner elections is studied in varying contexts. For instance, diversity of candidates and representation of voters are both separately termed as being fair. A common denominator to ensure fairness across all such contexts…

Computer Science and Game Theory · Computer Science 2022-11-24 Kunal Relia

Artificial Intelligence (AI) has been used extensively in automatic decision making in a broad variety of scenarios, ranging from credit ratings for loans to recommendations of movies. Traditional design guidelines for AI models focus…

Artificial Intelligence · Computer Science 2018-09-27 Marisa Vasconcelos , Carlos Cardonha , Bernardo Gonçalves

Mechanism design is concerned with settings where a policymaker (or social planner) faces the problem of aggregating the announced preferences of multiple agents into a collective (or social), system-wide decision. One of the most important…

Multiagent Systems · Computer Science 2020-03-02 Mohammad Ali Javidian , Pooyan Jamshidi , Marco Valtorta , Rasoul Ramezanian

Political candidates often shift their positions opportunistically in hopes of capturing more votes. When there are only two candidates, the best strategy for each of them is often to move towards the other. This eventually results in two…

Dynamical Systems · Mathematics 2023-10-25 Christoph Börgers , Bruce Boghosian , Natasa Dragovic , Anna Haensch

In this work we study the metric distortion problem in voting theory under a limited amount of ordinal information. Our primary contribution is threefold. First, we consider mechanisms which perform a sequence of pairwise comparisons…

Computer Science and Game Theory · Computer Science 2021-07-07 Ioannis Anagnostides , Dimitris Fotakis , Panagiotis Patsilinakos

We consider a setting with agents that have preferences over alternatives and are partitioned into disjoint districts. The goal is to choose one alternative as the winner using a mechanism which first decides a representative alternative…

Computer Science and Game Theory · Computer Science 2023-01-10 Aris Filos-Ratsikas , Alexandros A. Voudouris

Traditionally, heuristic methods are used to generate candidates for large scale recommender systems. Model-based candidate generation promises multiple potential advantages, primarily that we can explicitly optimize the same objective as…

Information Retrieval · Computer Science 2021-05-20 Alim Virani , Jay Baxter , Dan Shiebler , Philip Gautier , Shivam Verma , Yan Xia , Apoorv Sharma , Sumit Binnani , Linlin Chen , Chenguang Yu