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In approval-based multiwinner voting, voters express approval preferences over a set of candidates, and the goal is to return a winning committee. This model captures a broad range of subset selection problems under preferences. Prior work…

Computer Science and Game Theory · Computer Science 2026-04-28 Niclas Boehmer , Luca Kreisel , Jannik Peters

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

Much of the theoretical work on strategic voting makes strong assumptions about what voters know about the voting situation. A strategizing voter is typically assumed to know how other voters will vote and to know the rules of the voting…

Multiagent Systems · Computer Science 2019-07-23 Wesley H. Holliday , Eric Pacuit

The voter model is a paradigm of ordering dynamics. At each time step, a random node is selected and copies the state of one of its neighbors. Traditionally, this state has been considered as a binary variable. Here, we relax this…

Statistical Mechanics · Physics 2015-06-05 Michele Starnini , Andrea Baronchelli , Romualdo Pastor-Satorras

By classic results in social choice theory, any reasonable preferential voting method sometimes gives individuals an incentive to report an insincere preference. The extent to which different voting methods are more or less resistant to…

Artificial Intelligence · Computer Science 2025-02-25 Wesley H. Holliday , Alexander Kristoffersen , Eric Pacuit

We study computational aspects of three prominent voting rules that use approval ballots to elect multiple winners. These rules are satisfaction approval voting, proportional approval voting, and reweighted approval voting. We first show…

Computer Science and Game Theory · Computer Science 2014-07-14 Haris Aziz , Serge Gaspers , Joachim Gudmundsson , Simon Mackenzie , Nicholas Mattei , Toby Walsh

In the face of adverse motives, it is indispensable to achieve a consensus. Elections have been the canonical way by which modern democracy has operated since the 17th century. Nowadays, they regulate markets, provide an engine for modern…

Machine Learning · Computer Science 2026-01-06 Hao Xiang Li , Yash Shah , Lorenzo Giusti

Triple Modular Redundancy (TMR) has been traditionally used to ensure complete tolerance to a single fault or a faulty processing unit, where the processing unit may be a circuit or a system. However, TMR incurs more than 200% overhead in…

Hardware Architecture · Computer Science 2023-11-02 P Balasubramanian , D L Maskell

This document describes a class of C functions implementing a distributed software voting mechanism for EPX or similar message passing multi-threaded environments. Such a tool may be used for example, to set up a restoring organ, i.e., an…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-10-10 Vincenzo De Florio

Redundancy is a fundamental characteristic of many biological processes such as those in the genetic, visual, muscular and nervous system; yet its function has not been fully understood. The conventional interpretation of redundancy is that…

Information Theory · Computer Science 2019-02-04 Anh Tuan Nguyen , Jian Xu , Diu Khue Luu , Qi Zhao , Zhi Yang

Citizen-focused democratic processes where participants deliberate on alternatives and then vote to make the final decision are increasingly popular today. While the computational social choice literature has extensively investigated voting…

Multiagent Systems · Computer Science 2023-05-17 Kanav Mehra , Nanda Kishore Sreenivas , Kate Larson

Modular Aerial Robotic Systems (MARS) consist of multiple drone units assembled into a single, integrated rigid flying platform. With inherent redundancy, MARS can self-reconfigure into different configurations to mitigate rotor or unit…

Robotics · Computer Science 2025-03-13 Rui Huang , Siyu Tang , Zhiqian Cai , Lin Zhao

Large statically indeterminate truss and frame structures exhibit complex load-bearing behavior, and redundancy matrices are helpful for their analysis and design. Depending on the task, the full redundancy matrix or only its diagonal…

Computational Engineering, Finance, and Science · Computer Science 2024-02-14 Anton Tkachuk , Tim Krake , Jan Gade , Malte von Scheven

In this paper, we study a fault-tolerant control for systems consisting of multiple homogeneous components such as parallel processing machines. This type of system is often more robust to uncertainty compared to those with a single…

Optimization and Control · Mathematics 2020-12-03 Jalal Arabneydi , Amir G. Aghdam

Mission-critical and safety-critical applications generally tend to incorporate triple modular redundancy (TMR) to embed fault tolerance in their physical implementations. In a TMR realization, an original function block, which may be a…

Hardware Architecture · Computer Science 2020-08-14 P Balasubramanian , D L Maskell , N E Mastorakis

We study a generalization of the voter model on complex networks, focusing on the scaling of mean exit time. Previous work has defined the voter model in terms of an initially chosen node and a randomly chosen neighbor, which makes it…

Statistical Mechanics · Physics 2015-05-13 Casey M. Schneider-Mizell , Leonard M. Sander

Modular robots can be reconfigured to create a variety of designs from a small set of components. But constructing a robot's hardware on its own is not enough -- each robot needs a controller. One could create controllers for some designs…

Robotics · Computer Science 2022-11-01 Julian Whitman , Howie Choset

Neural Module Networks (NMN) are a compelling method for visual question answering, enabling the translation of a question into a program consisting of a series of reasoning sub-tasks that are sequentially executed on the image to produce…

Computation and Language · Computer Science 2023-10-25 Wafa Aissa , Marin Ferecatu , Michel Crucianu

Neural module networks (NMNs) are a popular approach for modeling compositionality: they achieve high accuracy when applied to problems in language and vision, while reflecting the compositional structure of the problem in the network…

Computation and Language · Computer Science 2020-09-09 Sanjay Subramanian , Ben Bogin , Nitish Gupta , Tomer Wolfson , Sameer Singh , Jonathan Berant , Matt Gardner

Artificial neural networks (NN) are instrumental in realizing highly-automated driving functionality. An overarching challenge is to identify best safety engineering practices for NN and other learning-enabled components. In particular,…

Machine Learning · Computer Science 2018-06-11 Chih-Hong Cheng , Georg Nührenberg , Chung-Hao Huang , Harald Ruess , Hirotoshi Yasuoka