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The empirical measure of an interacting particle system is a purely atomic random probability measure. In the limit as the number of particles grows to infinity, we show for McKean-Vlasov systems with common noise that this measure becomes…

Probability · Mathematics 2025-09-01 Robert Alexander Crowell

For centuries, it has been widely believed that the influence of a small coalition of voters is negligible in a large election. Consequently, there is a large body of literature on characterizing the likelihood for an election to be…

Theoretical Economics · Economics 2023-06-13 Lirong Xia

Many phenomena can be modeled as network dynamics with punctuate interactions. However, most relevant dynamics do not allow for computational tractability. To circumvent this difficulty, the Poisson Hypothesis regime replaces interaction…

Probability · Mathematics 2024-03-22 Michel Davydov

When playing games in groups, it is an advantage for individuals to have accurate statistical information on the strategies of their opponents. Such information may be obtained by remembering previous interactions. We consider a…

Adaptation and Self-Organizing Systems · Physics 2015-10-14 James Burridge

A key challenge of evolutionary game theory and multi-agent learning is to characterize the limit behavior of game dynamics. Whereas convergence is often a property of learning algorithms in games satisfying a particular reward structure…

Computer Science and Game Theory · Computer Science 2022-02-09 Aleksander Czechowski , Georgios Piliouras

We study incentive designs for a class of stochastic Stackelberg games with one leader and a large number of (finite as well as infinite population of) followers. We investigate whether the leader can craft a strategy under a dynamic…

Computer Science and Game Theory · Computer Science 2024-02-13 Sina Sanjari , Subhonmesh Bose , Tamer Başar

Motivated by applications where impatience is pervasive and evaluation times are uncertain, we study a selection model where options may expire at an unknown point in time and evaluation times are stochastic. Initially, the decision-maker…

Optimization and Control · Mathematics 2026-02-05 Yihua Xu , Rohan Ghuge , Sebastian Perez-Salazar

We introduce and analyze a class of interacting particle systems on the real line that combine features of the stochastic rat race and (deterministic) follow-the-leader models. The particle system evolves as a continuous-time pure jump…

Probability · Mathematics 2026-01-07 Sayan Banerjee , Amarjit Budhiraja , Dilshad Imon

Studying distributed computing through the lens of algebraic topology has been the source of many significant breakthroughs during the last two decades, especially in the design of lower bounds or impossibility results for deterministic…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-05-26 Pierre Fraigniaud , Ran Gelles , Zvi Lotker

We study several fundamental properties of a class of stochastic processes called spatial Lambda-coalescents. In these models, a number of particles perform independent random walks on some underlying graph G. In addition, particles on the…

Probability · Mathematics 2010-01-21 Omer Angel , Nathanael Berestycki , Vlada Limic

We consider a load balancing model where a Poisson stream of jobs arrive at a system of many servers whose service time distribution possesses a finite second moment. A small fraction of arrivals pass through the so called power-of-choice…

Probability · Mathematics 2024-04-16 Rami Atar , Gershon Wolansky

Building upon the one-step replica symmetry breaking formalism, duly understood and ramified, we show that the sequence of ordered extreme values of a general class of Euclidean-space logarithmically correlated random energy models…

Statistical Mechanics · Physics 2016-12-20 Xiangyu Cao , Yan V. Fyodorov , Pierre Le Doussal

Population protocols are a popular model of distributed computing, in which randomly-interacting agents with little computational power cooperate to jointly perform computational tasks. Inspired by developments in molecular computation, and…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-04-18 Dan Alistarh , James Aspnes , David Eisenstat , Rati Gelashvili , Ronald L. Rivest

We consider the leader election problem in population protocol models. In pragmatic settings of population protocols, self-stabilization is a highly desired feature owing to its fault resilience and the benefit of initialization freedom.…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-05-21 Yuichi Sudo , Ryota Eguchi , Taisuke Izumi , Toshimitsu Masuzawa

In a coalescing random walk, a set of particles make independent random walks on a graph. Whenever one or more particles meet at a vertex, they unite to form a single particle, which then continues the random walk through the graph.…

Data Structures and Algorithms · Computer Science 2016-12-28 Colin Cooper , Robert Elsasser , Hirotaka Ono , Tomasz Radzik

We study the phenomenon of intransitivity in models of dice and voting. First, we follow a recent thread of research for $n$-sided dice with pairwise ordering induced by the probability, relative to $1/2$, that a throw from one die is…

Probability · Mathematics 2020-10-27 Jan Hązła , Elchanan Mossel , Nathan Ross , Guangqu Zheng

In this work we study the metric distortion problem in voting theory under a limited amount of ordinal information. Our primary contribution is threefold. First, we consider mechanisms which perform a sequence of pairwise comparisons…

Computer Science and Game Theory · Computer Science 2021-07-07 Ioannis Anagnostides , Dimitris Fotakis , Panagiotis Patsilinakos

Suppose that a point-like steady source at $x=0$ injects particles into a half-infinite line. The particles diffuse and die. At long times a non-equilibrium steady state sets in, and we assume that it involves many particles. If the…

Statistical Mechanics · Physics 2015-12-07 Baruch Meerson

We study the convergence of a random iterative sequence of a family of operators on infinite dimensional Hilbert spaces, inspired by the Stochastic Gradient Descent (SGD) algorithm in the case of the noiseless regression, as studied in [1].…

Functional Analysis · Mathematics 2022-09-02 Soumyadip Ghosh , Yingdong Lu , Tomasz J. Nowicki

In the stochastic population protocol model, we are given a connected graph with $n$ nodes, and in every time step, a scheduler samples an edge of the graph uniformly at random and the nodes connected by this edge interact. A fundamental…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-12-22 Dan Alistarh , Joel Rybicki , Sasha Voitovych
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