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While several classes of integer linear optimization problems are known to be solvable in polynomial time, far fewer tractability results exist for integer nonlinear optimization. In this work, we narrow this gap by identifying a broad…

Optimization and Control · Mathematics 2026-02-09 Alberto Del Pia

Distributed optimization algorithms have been studied extensively in the literature; however, underlying most algorithms is a linear consensus scheme, i.e. averaging variables from neighbors via doubly stochastic matrices. We consider…

Optimization and Control · Mathematics 2023-03-14 Hsu Kao , Vijay Subramanian

A team consisting of an unknown number of mobile agents, starting from different nodes of an unknown network, possibly at different times, have to meet at the same node. Agents are anonymous (identical), execute the same deterministic…

Data Structures and Algorithms · Computer Science 2016-03-15 Yoann Dieudonné , Andrzej Pelc

The apportionment problem constitutes a fundamental problem in democratic societies: How to distribute a fixed number of seats among a set of states in proportion to the states' populations? This--seemingly simple--task has led to a rich…

Computer Science and Game Theory · Computer Science 2024-11-01 Javier Cembrano , José Correa , Ulrike Schmidt-Kraepelin , Alexandros Tsigonias-Dimitriadis , Victor Verdugo

Population protocols are a relatively novel computational model in which very resource-limited anonymous agents interact in pairs with the goal of computing predicates. We consider the probabilistic version of this model, which naturally…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-09-20 Vladyslav Melnychuk

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

Nearest neighbor is a popular nonparametric method for classification and regression with many appealing properties. In the big data era, the sheer volume and spatial/temporal disparity of big data may prohibit centrally processing and…

Statistics Theory · Mathematics 2018-12-13 Jiexin Duan , Xingye Qiao , Guang Cheng

Reasoning under uncertainty is a fundamental challenge in Artificial Intelligence. As with most of these challenges, there is a harsh dilemma between the expressive power of the language used, and the tractability of the computational…

Artificial Intelligence · Computer Science 2025-05-08 Luise Ge , Brendan Juba , Kris Nilsson

We address discrete-time consensus on the Euclidean unit sphere. For this purpose we consider a distributed algorithm comprising the iterative projection of a conical combination of neighboring states. Neighborhoods are represented by a…

Optimization and Control · Mathematics 2026-01-19 Johan Thunberg , Galina Sidorenko

Logics with team semantics provide alternative means for logical characterization of complexity classes. Both dependence and independence logic are known to capture non-deterministic polynomial time, and the frontiers of tractability in…

Logic in Computer Science · Computer Science 2019-03-27 Miika Hannula , Lauri Hella

Motivated by the difficulty of specifying complete ordinal preferences over a large set of $m$ candidates, we study voting rules that are computable by querying voters about $t < m$ candidates. Generalizing prior works that focused on…

Computer Science and Game Theory · Computer Science 2024-09-30 Daniel Halpern , Safwan Hossain , Jamie Tucker-Foltz

This paper studies fundamental limitations of performance for distributed decision-making in robotic networks. The class of decision-making problems we consider encompasses a number of prototypical problems such as average-based consensus…

Multiagent Systems · Computer Science 2017-08-15 Federico Rossi , Marco Pavone

The effectiveness of collective decision-making is often challenged by the bounded rationality and inherent stochasticity of individual agents. We investigate this by analyzing how to aggregate decisions from n experts, each receiving a…

Computer Science and Game Theory · Computer Science 2026-03-17 Zhihuan Huang , Yichong Xia , Yuqing Kong

We consider the problem of distributed learning, where a network of agents collectively aim to agree on a hypothesis that best explains a set of distributed observations of conditionally independent random processes. We propose a…

Optimization and Control · Mathematics 2017-04-12 Angelia Nedić , Alex Olshevsky , César A. Uribe

This note is concerned with a formal analysis of the problem of non-monotonic reasoning in intelligent systems, especially when the uncertainty is taken into account in a quantitative way. A firm connection between logic and probability is…

Artificial Intelligence · Computer Science 2013-04-05 Hung-Trung Nguyen

Voting is a very general method of preference aggregation. A voting rule takes as input every voter's vote (typically, a ranking of the alternatives), and produces as output either just the winning alternative or a ranking of the…

Computer Science and Game Theory · Computer Science 2012-07-09 Vincent Conitzer , Tuomas Sandholm

We study opinion dynamics in a population of interacting adaptive agents voting on a set of complex multidimensional issues. We consider agents which can classify issues into for or against. The agents arrive at the opinions about each…

Physics and Society · Physics 2009-03-11 Renato Vicente , Andre C. R. Martins , Nestor Caticha

Unlimited asynchronism is intolerable in real physically distributed computer systems. Such systems, synchronous or not, use clocks and timeouts. Therefore the magnitudes of elapsed absolute time in the system need to satisfy the axiom of…

Distributed, Parallel, and Cluster Computing · Computer Science 2009-06-04 Paul M. B. Vitanyi

We study the problem of making predictions of an adversarially chosen high-dimensional state that are unbiased subject to an arbitrary collection of conditioning events, with the goal of tailoring these events to downstream decision makers.…

Machine Learning · Computer Science 2023-10-30 Georgy Noarov , Ramya Ramalingam , Aaron Roth , Stephan Xie

Manipulation, bribery, and control are well-studied ways of changing the outcome of an election. Many voting rules are, in the general case, computationally resistant to some of these manipulative actions. However when restricted to…

Computational Complexity · Computer Science 2017-07-24 Gábor Erdélyi , Martin Lackner , Andreas Pfandler