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Related papers: Vote Elicitation: Complexity and Strategy-Proofnes…

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We study the election control problem with multi-votes, where each voter can present a single vote according different views (or layers, we use "layer" to represent "view"). For example, according to the attributes of candidates, such as:…

Computational Complexity · Computer Science 2023-07-03 Fengbo Wang , Aizhong Zhou , Jianliang Xu

We consider an agent community wishing to decide on several binary issues by means of issue-by-issue majority voting. For each issue and each agent, one of the two options is better than the other. However, some of the agents may be…

Computer Science and Game Theory · Computer Science 2022-07-12 Shiri Alouf-Heffetz , Laurent Bulteau , Edith Elkind , Nimrod Talmon , Nicholas Teh

We introduce and study the weakly single-crossing domain on trees which is a generalization of the well-studied single-crossing domain in social choice theory. We design a polynomial-time algorithm for recognizing preference profiles which…

Multiagent Systems · Computer Science 2025-07-25 Palash Dey

Voting theory has become increasingly integrated with computational social choice and multiagent systems. Computational complexity has been extensively used as a shield against manipulation of voting systems, however for several voting…

Computer Science and Game Theory · Computer Science 2011-08-24 Curtis Menton , Preetjot Singh

In many real world situations, collective decisions are made using voting. Moreover, scenarios such as committee or board elections require voting rules that return multiple winners. In multi-winner approval voting (AV), an agent may vote…

Computer Science and Game Theory · Computer Science 2019-05-31 Jaelle Scheuerman , Jason L. Harman , Nicholas Mattei , K. Brent Venable

It is important to collect credible training samples $(x,y)$ for building data-intensive learning systems (e.g., a deep learning system). Asking people to report complex distribution $p(x)$, though theoretically viable, is challenging in…

Machine Learning · Computer Science 2021-02-26 Jiaheng Wei , Zuyue Fu , Yang Liu , Xingyu Li , Zhuoran Yang , Zhaoran Wang

The Possible-Winner problem asks, given an election where the voters' preferences over the set of candidates is partially specified, whether a distinguished candidate can become a winner. In this work, we consider the computational…

Computer Science and Game Theory · Computer Science 2018-02-27 Batya Kenig

In the computational social choice literature, there has been great interest in understanding how computational complexity can act as a barrier against manipulation of elections. Much of this literature, however, makes the assumption that…

Computer Science and Game Theory · Computer Science 2015-07-27 Vijay Menon , Kate Larson

AI agents are commonly trained with large datasets of demonstrations of human behavior. However, not all behaviors are equally safe or desirable. Desired characteristics for an AI agent can be expressed by assigning desirability scores,…

Machine Learning · Computer Science 2024-05-08 Tim Franzmeyer , Edith Elkind , Philip Torr , Jakob Foerster , Joao Henriques

We introduce and study a computational version of the principal-agent problem -- a classic problem in Economics that arises when a principal desires to contract an agent to carry out some task, but has incomplete information about the agent…

Computer Science and Game Theory · Computer Science 2023-05-18 David Hyland , Julian Gutierrez , Michael Wooldridge

Single-peakedness is one of the most important and well-known domain restrictions on preferences. The computational study of single-peaked electorates has largely been restricted to elections with tie-free votes, and recent work that…

Computer Science and Game Theory · Computer Science 2016-06-21 Zack Fitzsimmons , Edith Hemaspaandra

In peer selection agents must choose a subset of themselves for an award or a prize. As agents are self-interested, we want to design algorithms that are impartial, so that an individual agent cannot affect their own chance of being…

Computer Science and Game Theory · Computer Science 2020-05-01 Nicholas Mattei , Paolo Turrini , Stanislav Zhydkov

Given a learning problem with real-world tradeoffs, which cost function should the model be trained to optimize? This is the metric selection problem in machine learning. Despite its practical interest, there is limited formal guidance on…

Machine Learning · Statistics 2022-08-22 Gaurush Hiranandani

We propose models for lobbying in a probabilistic environment, in which an actor (called "The Lobby") seeks to influence voters' preferences of voting for or against multiple issues when the voters' preferences are represented in terms of…

Computational Complexity · Computer Science 2011-03-01 Daniel Binkele-Raible , Gábor Erdélyi , Henning Fernau , Judy Goldsmith , Nicholas Mattei , Jörg Rothe

Preference queries incorporate the notion of binary preference relation into relational database querying. Instead of returning all the answers, such queries return only the best answers, according to a given preference relation. Preference…

Databases · Computer Science 2010-09-01 Denis Mindolin , Jan Chomicki

A key distinguishing feature of conversational recommender systems over traditional recommender systems is their ability to elicit user preferences using natural language. Currently, the predominant approach to preference elicitation is to…

Information Retrieval · Computer Science 2025-04-09 Ivica Kostric , Krisztian Balog , Filip Radlinski

Recent advances in multi-task peer prediction have greatly expanded our knowledge about the power of multi-task peer prediction mechanisms. Various mechanisms have been proposed in different settings to elicit different types of…

Computer Science and Game Theory · Computer Science 2021-06-08 Shuran Zheng , Fang-Yi Yu , Yiling Chen

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

Formal verification of multi-agent systems is hard, both theoretically and in practice. In particular, studies that use a single verification technique typically show limited efficiency, and allow to verify only toy examples. Here, we…

Many electoral bribery, control, and manipulation problems (which we will refer to in general as "manipulative actions" problems) are NP-hard in the general case. It has recently been noted that many of these problems fall into polynomial…

Computer Science and Game Theory · Computer Science 2012-07-09 Piotr Faliszewski , Edith Hemaspaandra , Lane A. Hemaspaandra