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We study the utilitarian distortion of social choice mechanisms under the recently proposed learning-augmented framework where some (possibly unreliable) predicted information about the preferences of the agents is given as input. In…

Computer Science and Game Theory · Computer Science 2025-02-11 Aris Filos-Ratsikas , Georgios Kalantzis , Alexandros A. Voudouris

Social media has been a paramount arena for election campaigns for political actors. While many studies have been paying attention to the political campaigns related to partisanship, politicians also can conduct different campaigns…

Computers and Society · Computer Science 2023-04-05 Taichi Murayama , Akira Matsui , Kunihiro Miyazaki , Yasuko Matsubara , Yasushi Sakurai

Complexity theory is a useful tool to study computational issues surrounding the elicitation of preferences, as well as the strategic manipulation of elections aggregating together preferences of multiple agents. We study here the…

Artificial Intelligence · Computer Science 2012-04-18 Toby Walsh

Selective rationalization has become a common mechanism to ensure that predictive models reveal how they use any available features. The selection may be soft or hard, and identifies a subset of input features relevant for prediction. The…

Computation and Language · Computer Science 2019-12-17 Mo Yu , Shiyu Chang , Yang Zhang , Tommi S. Jaakkola

We consider the two-sided stable matching setting in which there may be uncertainty about the agents' preferences due to limited information or communication. We consider three models of uncertainty: (1) lottery model --- in which for each…

Computer Science and Game Theory · Computer Science 2016-07-12 Haris Aziz , Péter Biró , Serge Gaspers , Ronald de Haan , Nicholas Mattei , Baharak Rastegari

The outcome of an election depends not only on which candidate is more popular, but also on how many of their voters actually turn out to vote. Here we consider a simple model in which voters abstain from voting if they think their vote…

Physics and Society · Physics 2021-12-01 Ekaterina Landgren , Jonas L. Juul , Steven H. Strogatz

Multi-winner voting plays a crucial role in selecting representative committees based on voter preferences. Previous research has predominantly focused on single-stage voting rules, which are susceptible to manipulation during preference…

Computer Science and Game Theory · Computer Science 2024-02-06 Shengjie Gong , Lingxiao Huang , Shuangping Huang , Yuyi Wang , Zhiqi Wang , Tao Xiao , Xiang Yan , Chunxue Yang

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

While manipulative attacks on elections have been well-studied, only recently has attention turned to attacks that account for geographic information, which are extremely common in the real world. The most well known in the media is…

Computer Science and Game Theory · Computer Science 2020-03-17 Zack Fitzsimmons , Omer Lev

Our hypothesis is that by equipping certain agents in a multi-agent system controlling an intelligent building with automated decision support, two important factors will be increased. The first is energy saving in the building. The second…

Artificial Intelligence · Computer Science 2013-01-30 Magnus Boman , Paul Davidsson , Hakan L. Younes

We consider a two-round election model involving $m$ voters and $n$ candidates. Each voter is endowed with a strict preference list ranking the candidates. In the first round, the candidates are partitioned into two subsets, $A$ and $B$,…

Computer Science and Game Theory · Computer Science 2026-03-17 Emilio De Santis , Antonio Di Crescenzo , Verdiana Mustaro

Proportional representation (PR) is a fundamental principle of many democracies world-wide which employ PR-based voting rules to elect their representatives. The normative properties of these voting rules however, are often only understood…

Computer Science and Game Theory · Computer Science 2018-01-30 Barton E. Lee

The notion of uncertainty is of major importance in machine learning and constitutes a key element of machine learning methodology. In line with the statistical tradition, uncertainty has long been perceived as almost synonymous with…

Machine Learning · Computer Science 2021-06-24 Eyke Hüllermeier , Willem Waegeman

Social influence profoundly impacts individual choices and collective behaviors in politics. In this work, driven by the goal of protecting elections from improper influence, we consider the following scenario: an individual, who has vested…

Social and Information Networks · Computer Science 2025-02-05 Dragos Ristache , Fabian Spaeh , Charalampos E. Tsourakakis

When consequential decisions are informed by algorithmic input, individuals may feel compelled to alter their behavior in order to gain a system's approval. Models of agent responsiveness, termed "strategic manipulation," analyze the…

Machine Learning · Computer Science 2019-05-13 Lily Hu , Nicole Immorlica , Jennifer Wortman Vaughan

[Spreadsheet] Models are invaluable tools for strategic planning. Models help key decision makers develop a shared conceptual understanding of complex decisions, identify sensitivity factors and test management scenarios. Different…

Human-Computer Interaction · Computer Science 2024-12-31 Paula Jennings

Most decision-making models, including the pairwise comparison method, assume the decision-makers honesty. However, it is easy to imagine a situation where a decision-maker tries to manipulate the ranking results. This paper presents three…

Artificial Intelligence · Computer Science 2024-10-11 Michał Strada , Sebastian Ernst , Jacek Szybowski , Konrad Kułakowski

A key promise of democratic voting is that, by accounting for all constituents' preferences, it produces decisions that benefit the constituency overall. It is alarming, then, that all deterministic voting rules have unbounded distortion:…

Computer Science and Game Theory · Computer Science 2023-05-22 Bailey Flanigan , Ariel D. Procaccia , Sven Wang

Decision-making methods very often use the technique of comparing alternatives in pairs. In this approach, experts are asked to compare different options, and then a quantitative ranking is created from the results obtained. It is commonly…

Artificial Intelligence · Computer Science 2025-04-21 M. Strada , K. Kułakowski

A cognitive radio system has the ability to observe and learn from the environment, adapt to the environmental conditions, and use the radio spectrum more efficiently. However, due to multipath fading, shadowing, or varying channel…

Information Theory · Computer Science 2017-01-20 Fatima Salahdine , Naima Kaabouch , Hassan Ghazi
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