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Related papers: Heuristics in Multi-Winner Approval Voting

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Inferential decision-making algorithms typically assume that an underlying probabilistic model of decision alternatives and outcomes may be learned a priori or online. Furthermore, when applied to robots in real-world settings they often…

Robotics · Computer Science 2023-09-15 Yucheng Chen , Pingping Zhu , Anthony Alers , Tobias Egner , Marc A. Sommer , Silvia Ferrari

We focus on the following natural question: is it possible to influence the outcome of a voting process through the strategic provision of information to voters who update their beliefs rationally? We investigate whether it is…

Computer Science and Game Theory · Computer Science 2019-09-24 Matteo Castiglioni , Andrea Celli , Nicola Gatti

Humans have come to rely on machines for reducing excessive information to manageable representations. But this reliance can be abused -- strategic machines might craft representations that manipulate their users. How can a user make good…

Machine Learning · Computer Science 2022-06-20 Vineet Nair , Ganesh Ghalme , Inbal Talgam-Cohen , Nir Rosenfeld

We propose a framework for strategic voting when a voter may lack knowledge about the preferences of other voters, or about other voters' knowledge about her own preference. In this setting we define notions of manipulation, equilibrium,…

Computer Science and Game Theory · Computer Science 2021-11-30 Zeinab Bakhtiari , Hans van Ditmarsch , Abdallah Saffidine

We study a variation of the minority game. There are N agents. Each has to choose between one of two alternatives everyday, and there is reward to each member of the smaller group. The agents cannot communicate with each other, but try to…

Trading and Market Microstructure · Quantitative Finance 2015-05-27 Deepak Dhar , V. Sasidevan , Bikas K. Chakrabarti

AI systems are often used to make or contribute to important decisions in a growing range of applications, including criminal justice, hiring, and medicine. Since these decisions impact human lives, it is important that the AI systems act…

Artificial Intelligence · Computer Science 2021-03-16 Duncan C McElfresh , Lok Chan , Kenzie Doyle , Walter Sinnott-Armstrong , Vincent Conitzer , Jana Schaich Borg , John P Dickerson

A key challenge in satisficing planning is to use multiple heuristics within one heuristic search. An aggregation of multiple heuristic estimates, for example by taking the maximum, has the disadvantage that bad estimates of a single…

Artificial Intelligence · Computer Science 2021-04-13 David Speck , André Biedenkapp , Frank Hutter , Robert Mattmüller , Marius Lindauer

Revealed preference theory studies the possibility of modeling an agent's revealed preferences and the construction of a consistent utility function. However, modeling agent's choices over preference orderings is not always practical and…

Machine Learning · Statistics 2018-02-21 Venkata Sriram Siddhardh Nadendla , Cedric Langbort

Despite extensive theoretical research on proportionality in approval-based multiwinner voting, its impact on which committees and candidates can be selected in practice remains poorly understood. We address this gap by (i) analyzing the…

Computer Science and Game Theory · Computer Science 2025-11-13 Niclas Boehmer , Lara Glessen , Jannik Peters

In approval voting, individuals vote for all platforms that they find acceptable. In this situation it is natural to ask: When is agreement possible? What conditions guarantee that some fraction of the voters agree on even a single…

Combinatorics · Mathematics 2021-08-30 Kristen Mazur , Mutiara Sondjaja , Matthew Wright , Carolyn Yarnall

Multi-winner voting rules based on approval ballots have received increased attention in recent years. In particular Satisfaction Approval Voting (SAV) and its variants have been proposed. In this note, we show that the winning set can be…

Computer Science and Game Theory · Computer Science 2015-01-12 Haris Aziz , Toby Walsh

Most analyses of manipulation of voting schemes have adopted two assumptions that greatly diminish their practical import. First, it is usually assumed that the manipulators have full knowledge of the votes of the nonmanipulating agents.…

Computer Science and Game Theory · Computer Science 2012-10-19 Tyler Lu , Pingzhong Tang , Ariel D. Procaccia , Craig Boutilier

The major finding, of this article, is an ensemble method, but more exactly, a novel, better ranked voting system (and other variations of it), that aims to solve the problem of finding the best candidate to represent the voters. We have…

Artificial Intelligence · Computer Science 2021-10-15 Gabriel-Claudiu Grama

Direct democracy is often proposed as a possible solution to the 21st-century problems of democracy. However, this suggestion clashes with the size and complexity of 21st-century societies, entailing an excessive cognitive burden on voters,…

Artificial Intelligence · Computer Science 2018-07-11 Umberto Grandi

In peer mechanisms, the competitors for a prize also determine who wins. Each competitor may be asked to rank, grade, or nominate peers for the prize. Since the prize can be valuable, such as financial aid, course grades, or an award at a…

Artificial Intelligence · Computer Science 2024-05-31 Matthew Olckers , Toby Walsh

Multi-agent systems have demonstrated exceptional performance in downstream tasks beyond diverse single agent baselines. A growing body of work has explored ways to improve their reasoning and collaboration, from vote, debate, to complex…

Artificial Intelligence · Computer Science 2026-02-13 Yu Yao , Jiayi Dong , Yang Yang , Ju Li , Yilun Du

Undesired bias afflicts both human and algorithmic decision making, and may be especially prevalent when information processing trade-offs incentivize the use of heuristics. One primary example is \textit{statistical discrimination} --…

When people pursue rewards in stochastic environments, they often match their choice frequencies to the observed target frequencies, even when this policy is demonstrably sub-optimal. We used a ``hide and seek'' task to evaluate this…

Neurons and Cognition · Quantitative Biology 2025-11-11 Peter DiBerardino , Britt Anderson

Motivated by the difficulty of specifying complete ordinal preferences over a large set of $m$ candidates, we study voting rules that are computable by querying voters about $t < m$ candidates. Generalizing prior works that focused on…

Computer Science and Game Theory · Computer Science 2024-09-30 Daniel Halpern , Safwan Hossain , Jamie Tucker-Foltz

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