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In this paper, we propose a framework to study a general class of strategic behavior in voting, which we call vote operations. We prove the following theorem: if we fix the number of alternatives, generate $n$ votes i.i.d. according to a…

Artificial Intelligence · Computer Science 2012-08-15 Lirong Xia

We formulate the problem of eliciting agents' preferences with the goal of finding a Kemeny ranking as a Dueling Bandits problem. Here the bandits' arms correspond to alternatives that need to be ranked and the feedback corresponds to a…

Machine Learning · Computer Science 2023-12-20 Anne-Marie George , Christos Dimitrakakis

The computational study of election problems generally focuses on questions related to the winner or set of winners of an election. But social preference functions such as Kemeny rule output a full ranking of the candidates (a consensus).…

Computer Science and Game Theory · Computer Science 2021-05-19 Zack Fitzsimmons , Edith Hemaspaandra

The Skating System, which originated from the scrutineering system in dance sport tournaments, can be formulated as a voting system: We introduce and formalize the Skating System Single (SkS, for short), a new voting system embedded into…

Computer Science and Game Theory · Computer Science 2025-12-01 Laryssa Horn , Paul Nüsken , Jörg Rothe , Tessa Seeger

While a large body of empirical results show that temporally-extended actions and options may significantly affect the learning performance of an agent, the theoretical understanding of how and when options can be beneficial in online…

Machine Learning · Computer Science 2017-04-18 Ronan Fruit , Alessandro Lazaric

Black-box optimization refers to the optimization problem whose objective function and/or constraint sets are either unknown, inaccessible, or non-existent. In many applications, especially with the involvement of humans, the only way to…

Eliciting a preference model involves asking a person, named decision-maker, a series of questions. We assume that these preferences can be represented by an additive value function. In this work, we query simultaneously two decision-makers…

Artificial Intelligence · Computer Science 2026-02-25 Vincent Auriau , Khaled Belahcene , Emmanuel Malherbe , Vincent Mousseau , Marc Pirlot

We study an online mixed discrete and continuous optimization problem where a decision maker interacts with an unknown environment for a number of $T$ rounds. At each round, the decision maker needs to first jointly choose a discrete and a…

Optimization and Control · Mathematics 2024-08-27 Lintao Ye , Ming Chi , Zhi-Wei Liu , Xiaoling Wang , Vijay Gupta

In multi-objective decision planning and learning, much attention is paid to producing optimal solution sets that contain an optimal policy for every possible user preference profile. We argue that the step that follows, i.e, determining…

Machine Learning · Computer Science 2018-02-22 Luisa M Zintgraf , Diederik M Roijers , Sjoerd Linders , Catholijn M Jonker , Ann Nowé

In many settings -- like market research and social choice -- people may be presented with unfamiliar options. Classical mechanisms may perform poorly because they fail to incentivize people to learn about these options, or worse, encourage…

Theoretical Economics · Economics 2025-07-22 Modibo K. Camara , Nicole Immorlica , Brendan Lucier

We study the $K$-armed contextual dueling bandit problem, a sequential decision making setting in which the learner uses contextual information to make two decisions, but only observes \emph{preference-based feedback} suggesting that one…

Machine Learning · Computer Science 2021-11-25 Aadirupa Saha , Akshay Krishnamurthy

Over the past two decades, the notion of implicit bias has come to serve as an important component in our understanding of discrimination in activities such as hiring, promotion, and school admissions. Research on implicit bias posits that…

Computers and Society · Computer Science 2018-01-12 Jon Kleinberg , Manish Raghavan

Ranking is one of the most fundamental problems in machine learning with applications in many branches of computer science such as: information retrieval systems, recommendation systems, machine translation and computational biology.…

Data Structures and Algorithms · Computer Science 2015-04-07 Krzysztof Choromanski

Eliciting the preferences of a set of agents over a set of alternatives is a problem of fundamental importance in social choice theory. Prior work on this problem has studied the query complexity of preference elicitation for the…

Computer Science and Game Theory · Computer Science 2016-04-19 Palash Dey , Neeldhara Misra

In this paper we consider multi-objective reinforcement learning where the objectives are balanced using preferences. In practice, the preferences are often given in an adversarial manner, e.g., customers can be picky in many applications.…

Machine Learning · Computer Science 2021-10-29 Jingfeng Wu , Vladimir Braverman , Lin F. Yang

This paper proposes a voting process in which voters allocate fractional votes to their expected utility in different domains: over proposals, other participants, and sets containing proposals and participants. This approach allows for a…

Social and Information Networks · Computer Science 2025-04-21 Yasushi Sakai , Parfait Atchade-Adelomou , Ryan Jiang , Luis Alonso , Kent Larson , Ken Suzuki

We present theoretical and empirical results demonstrating the usefulness of voting rules for participatory democracies. We first give algorithms which efficiently elicit \epsilon-approximations to two prominent voting rules: the Borda rule…

Multiagent Systems · Computer Science 2014-07-17 David Lee , Ashish Goel , Tanja Aitamurto , Helene Landemore

In this paper, we study the problem of Participatory Budgeting (PB) with approval ballots, inspired by Multi-Winner Voting schemes. We present generalized preference aggregation methods for participatory budgeting, especially for finding…

Computational Engineering, Finance, and Science · Computer Science 2024-10-10 Rutvik Page , Arnav Doifode , Jitendra Tembhurne , Aishwarya Sagar Anand Ukey

We elicit incomplete preferences over monetary gambles with subjective uncertainty. Subjects rank gambles, and these rankings are used to estimate preferences; payments are based on estimated preferences. About 40\% of subjects express…

General Economics · Economics 2022-10-06 Kirby Nielsen , Luca Rigotti

Understanding when and how computational complexity can be used to protect elections against different manipulative actions has been a highly active research area over the past two decades. A recent body of work, however, has shown that…

Computer Science and Game Theory · Computer Science 2015-11-26 Vijay Menon , Kate Larson
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