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We study the manipulability of social choice correspondences in situations where individuals have incomplete information about others' preferences. We propose a general concept of manipulability that depends on the extension rule used to…

Theoretical Economics · Economics 2025-12-16 Raffaele Berzi , Daniela Bubboloni , Michele Gori

We investigate approval-based committee voting with incomplete information about the approval preferences of voters. We consider several models of incompleteness where each voter partitions the set of candidates into approved, disapproved,…

Computer Science and Game Theory · Computer Science 2024-08-21 Aviram Imber , Jonas Israel , Markus Brill , Benny Kimelfeld

Computational preference elicitation methods are tools used to learn people's preferences quantitatively in a given context. Recent works on preference elicitation advocate for active learning as an efficient method to iteratively construct…

Human-Computer Interaction · Computer Science 2024-07-29 Vijay Keswani , Vincent Conitzer , Hoda Heidari , Jana Schaich Borg , Walter Sinnott-Armstrong

We study computational problems for two popular parliamentary voting procedures: the amendment procedure and the successive procedure. While finding successful manipulations or agenda controls is tractable for both procedures, our…

Computer Science and Game Theory · Computer Science 2015-09-09 Robert Bredereck , Jiehua Chen , Rolf Niedermeier , Toby Walsh

In the context of computational social choice, we study voting methods that assign a set of winners to each profile of voter preferences. A voting method satisfies the property of positive involvement (PI) if for any election in which a…

Computer Science and Game Theory · Computer Science 2021-06-23 Wesley H. Holliday , Eric Pacuit

We study the control complexity of fallback voting. Like manipulation and bribery, electoral control describes ways of changing the outcome of an election; unlike manipulation or bribery attempts, control actions---such as…

Computer Science and Game Theory · Computer Science 2010-04-21 Gábor Erdélyi , Lena Piras , Jörg Rothe

Strategic manipulation of elections is typically studied in the context of promoting individual candidates. In parliamentary elections, however, the focus shifts: voters may care more about the overall governing coalition than the…

Computer Science and Game Theory · Computer Science 2026-01-13 Hodaya Barr , Eden Hartman , Yonatan Aumann , Sarit Kraus

Counterfactual regret minimization (CFR) is a family of iterative algorithms that are the most popular and, in practice, fastest approach to approximately solving large imperfect-information games. In this paper we introduce novel CFR…

Computer Science and Game Theory · Computer Science 2019-02-22 Noam Brown , Tuomas Sandholm

We study multiwinner elections with approval-based preferences. An instance of a multiwinner election consists of a set of alternatives, a population of voters---each voter approves a subset of alternatives, and the desired committee size…

Computer Science and Game Theory · Computer Science 2019-10-15 Piotr Skowron

We examine strategy-proof elections to select a winner amongst a set of agents, each of whom cares only about winning. This impartial selection problem was introduced independently by Holzman and Moulin and Alon et al. Fisher and Klimm…

Computer Science and Game Theory · Computer Science 2014-08-01 Nicolas Bousquet , Sergey Norin , Adrian Vetta

In the theory of voting, the Plurality rule for preferences that come in the form of linear orders selects the alternatives most frequently appearing in the first position of those orders, while the Anti-Plurality rule selects the…

Computer Science and Game Theory · Computer Science 2026-05-21 Ulle Endriss , Federico Fioravanti

We give new bounds for the single-nomination model of impartial selection, a problem proposed by Holzman and Moulin (Econometrica, 2013). A selection mechanism, which may be randomized, selects one individual from a group of $n$ based on…

Computer Science and Game Theory · Computer Science 2023-05-18 Javier Cembrano , Felix Fischer , Max Klimm

We study algorithms for average-cost reinforcement learning problems with value function approximation. Our starting point is the recently proposed POLITEX algorithm, a version of policy iteration where the policy produced in each iteration…

Machine Learning · Computer Science 2019-08-29 Yasin Abbasi-Yadkori , Nevena Lazic , Csaba Szepesvari , Gellert Weisz

In collective decision making, where a voting rule is used to take a collective decision among a group of agents, manipulation by one or more agents is usually considered negative behavior to be avoided, or at least to be made…

Artificial Intelligence · Computer Science 2013-03-05 Umberto Grandi , Andrea Loreggia , Francesca Rossi , Kristen Brent Venable , Toby Walsh

We address the problem of active online assortment optimization problem with preference feedback, which is a framework for modeling user choices and subsetwise utility maximization. The framework is useful in various real-world applications…

Machine Learning · Computer Science 2024-03-01 Aadirupa Saha , Pierre Gaillard

Constructive election control considers the problem of an adversary who seeks to sway the outcome of an electoral process in order to ensure that their favored candidate wins. We consider the computational problem of constructive election…

Computer Science and Game Theory · Computer Science 2019-12-02 Jasper Lu , David Kai Zhang , Zinovi Rabinovich , Svetlana Obraztsova , Yevgeniy Vorobeychik

We analyse strategic, complete information, sequential voting with ordinal preferences over the alternatives. We consider several voting mechanisms: plurality voting and approval voting with deterministic or uniform tie-breaking rules. We…

Computer Science and Game Theory · Computer Science 2019-04-19 Oren Dean , Yakov Babichenko , Moshe Tennenholtz

A central theme in computational social choice is to study the extent to which voting systems computationally resist manipulative attacks seeking to influence the outcome of elections, such as manipulation (i.e., strategic voting), control,…

Computer Science and Game Theory · Computer Science 2013-07-30 Piotr Faliszewski , Yannick Reisch , Jörg Rothe , Lena Schend

We consider the setting of iterative learning control, or model-based policy learning in the presence of uncertain, time-varying dynamics. In this setting, we propose a new performance metric, planning regret, which replaces the standard…

Machine Learning · Computer Science 2021-03-01 Naman Agarwal , Elad Hazan , Anirudha Majumdar , Karan Singh

We introduce a general problem about bribery in voting systems. In the $\mathcal{R}$-Multi-Bribery problem, the goal is to bribe a set of voters at minimum cost such that a desired candidate wins the perturbed election under the voting rule…

Data Structures and Algorithms · Computer Science 2018-12-06 Dušan Knop , Martin Koutecký , Matthias Mnich