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Mathematical optimization, although often leading to NP-hard models, is now capable of solving even large-scale instances within reasonable time. However, the primary focus is often placed solely on optimality. This implies that while…

Optimization and Control · Mathematics 2025-12-23 Kevin-Martin Aigner , Marc Goerigk , Michael Hartisch , Frauke Liers , Arthur Miehlich , Florian Rösel

Hedonic games model settings in which a set of agents have to be partitioned into groups which we call coalitions. In the enemy aversion model, each agent has friends and enemies, and an agent prefers to be in a coalition with as few…

Computer Science and Game Theory · Computer Science 2025-02-20 Martin Durand , Laurin Erlacher , Johanne Müller Vistisen , Sofia Simola

We argue that parameterized complexity is a useful tool with which to study global constraints. In particular, we show that many global constraints which are intractable to propagate completely have natural parameters which make them…

Artificial Intelligence · Computer Science 2009-03-04 Christian Bessiere , Emmanuel Hebrard , Brahim Hnich , Zeynep Kiziltan , Toby Walsh

We investigate two systems of fully proportional representation suggested by Chamberlin Courant and Monroe. Both systems assign a representative to each voter so that the "sum of misrepresentations" is minimized. The winner determination…

Computer Science and Game Theory · Computer Science 2014-02-05 Nadja Betzler , Arkadii Slinko , Johannes Uhlmann

We analyze the run-time complexity of computing allocations that are both fair and maximize the utilitarian social welfare, defined as the sum of agents' utilities. We focus on two tractable fairness concepts: envy-freeness up to one item…

Computer Science and Game Theory · Computer Science 2024-09-23 Haris Aziz , Xin Huang , Nicholas Mattei , Erel Segal-Halevi

Many dynamic decision problems, such as robotic control, involve a series of tasks, many of which are unknown at training time. Typical approaches for these problems, such as multi-task and meta reinforcement learning, do not generalize…

Machine Learning · Computer Science 2025-05-28 Luise Ge , Michael Lanier , Anindya Sarkar , Bengisu Guresti , Chongjie Zhang , Yevgeniy Vorobeychik

When selecting a subset of candidates (a so-called committee) based on the preferences of voters, proportional representation is often a major desideratum. When going beyond simplistic models such as party-list or district-based elections,…

Computer Science and Game Theory · Computer Science 2023-02-07 Markus Brill , Jannik Peters

In many applications such as rationing medical care and supplies, university admissions, and the assignment of public housing, the decision of who receives an allocation can be justified by various normative criteria. Such settings have…

Computer Science and Game Theory · Computer Science 2023-05-30 Siddhartha Banerjee , Matthew Eichhorn , David Kempe

Control and manipulation are two of the most studied types of attacks on elections. In this paper, we study the complexity of control attacks on elections in which there are manipulators. We study both the case where the "chair" who is…

Computer Science and Game Theory · Computer Science 2017-06-09 Zack Fitzsimmons , Edith Hemaspaandra , Lane A. Hemaspaandra

The Conditional Preference Network (CP-net) graphically represents user's qualitative and conditional preference statements under the ceteris paribus interpretation. The constrained CP-net is an extension of the CP-net, to a set of…

Artificial Intelligence · Computer Science 2021-09-28 Sultan Ahmed , Malek Mouhoub

We present a polynomial-time algorithm for computing an optimal committee of size $k$ under any given Thiele voting rule for elections on the Voter Interval domain (i.e., when voters can be ordered so that each candidate is approved by a…

Computer Science and Game Theory · Computer Science 2026-04-08 Pasin Manurangsi , Krzysztof Sornat

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

We consider the approval-based model of elections, and undertake a computational study of voting rules which select committees whose size is not predetermined. While voting rules that output committees with a predetermined number of winning…

Computer Science and Game Theory · Computer Science 2017-11-20 Piotr Faliszewski , Arkadii Slinko , Nimrod Talmon

We consider the problem of allocating applicants to courses, where each applicant has a subset of acceptable courses that she ranks in strict order of preference. Each applicant and course has a capacity, indicating the maximum number of…

Data Structures and Algorithms · Computer Science 2017-07-11 Katarina Cechlarova , Bettina Klaus , David F. Manlove

This paper addresses the problem of quantifying diversity for a set of objects. First, we conduct a systematic review of existing diversity measures and explore their undesirable behavior in certain cases. Based on this review, we formulate…

Machine Learning · Computer Science 2025-06-17 Mikhail Mironov , Liudmila Prokhorenkova

We consider generalizations of the classical secretary problem, also known as the problem of optimal choice, to posets where the only information we have is the size of the poset and the number of maximal elements. We show that, given this…

Combinatorics · Mathematics 2012-06-29 Bryn Garrod , Robert Morris

Partitioning a region into districts to favor a particular candidate or a party is commonly known as gerrymandering. In this paper, we investigate the gerrymandering problem in graph theoretic setting as proposed by Cohen-Zemach et al.…

Data Structures and Algorithms · Computer Science 2021-05-26 Sushmita Gupta , Pallavi Jain , Fahad Panolan , Sanjukta Roy , Saket Saurabh

We study set selection problems where the weights are uncertain. Instead of its exact weight, only an uncertainty interval containing its true weight is available for each element. In some cases, some solutions are universally optimal;…

Data Structures and Algorithms · Computer Science 2024-04-29 Christoph Dürr , Arturo Merino , José A. Soto , José Verschae

This paper studies the unification problem with associative, commutative, and associative-commutative functions mainly from a viewpoint of the parameterized complexity on the number of variables. It is shown that both associative and…

Symbolic Computation · Computer Science 2013-10-04 Tatsuya Akutsu , Takeyuki Tamura , Atsuhiro Takasu

Suppose that $n$ items arrive online in random order and the goal is to select $k$ of them such that the expected sum of the selected items is maximized. The decision for any item is irrevocable and must be made on arrival without knowing…

Data Structures and Algorithms · Computer Science 2020-12-02 Susanne Albers , Leon Ladewig