Search Results for author: Julien M. Hendrickx

Found 7 papers, 1 papers with code

Convergence, Consensus and Dissensus in the Weighted-Median Opinion Dynamics

no code implementations17 Dec 2022 Wenjun Mei, Julien M. Hendrickx, Ge Chen, Francesco Bullo, Florian Dörfler

Moreover, we prove a necessary and sufficient graph-theoretic condition for the almost-sure convergence to consensus, as well as a sufficient graph-theoretic condition for almost-sure persistent dissensus.

Minimax Multi-Agent Persistent Monitoring of a Network System

no code implementations17 Jan 2022 Samuel C. Pinto, Shirantha Welikala, Sean B. Andersson, Julien M. Hendrickx, Christos G. Cassandras

For a given visiting sequence, we prove that in an optimal dwelling time allocation the peak uncertainty is the same among all the targets.

Traveling Salesman Problem

2-D Directed Formation Control Based on Bipolar Coordinates

no code implementations2 Aug 2021 Farhad Mehdifar, Charalampos P. Bechlioulis, Julien M. Hendrickx, Dimos V. Dimarogonas

This work proposes a novel 2-D formation control scheme for acyclic triangulated directed graphs (a class of minimally acyclic persistent graphs) based on bipolar coordinates with (almost) global convergence to the desired shape.

A Semidefinite Programming Approach to Discrete-time Infinite Horizon Persistent Monitoring

no code implementations1 Apr 2021 Samuel C. Pinto, Sean B. Andersson, Julien M. Hendrickx, Christos G. Cassandras

We investigate the problem of persistent monitoring, where a mobile agent has to survey multiple targets in an environment in order to estimate their internal states.

Are energy savings the only reason for the emergence of bird echelon formation?

no code implementations24 Mar 2021 Mingming Shi, Julien M. Hendrickx

We analyze the conditions under which the emergence of frequently observed echelon formation can be explained solely by the maximization of energy savings.

Position

Graph Resistance and Learning from Pairwise Comparisons

no code implementations1 Feb 2019 Julien M. Hendrickx, Alex Olshevsky, Venkatesh Saligrama

The algorithm has a relative error decay that scales with the square root of the graph resistance, and provide a matching lower bound (up to log factors).

Exact worst-case convergence rates of the proximal gradient method for composite convex minimization

1 code implementation11 May 2017 Adrien B. Taylor, Julien M. Hendrickx, François Glineur

We establish the exact worst-case convergence rates of the proximal gradient method in this setting for any step size and for different standard performance measures: objective function accuracy, distance to optimality and residual gradient norm.

Optimization and Control

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