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What and Who

Pooling or Sampling: Collective Dynamics for Electrical Flow Estimation

Emanuele Natale
Max-Planck-Institut für Informatik - D1
AG1 Mittagsseminar (own work)
AG 1  
AG Audience
English

Date, Time and Location

Thursday, 24 May 2018
13:00
30 Minutes
E1 4
024
Saarbrücken

Abstract

The computation of electrical flows is a crucial primitive for many recently proposed optimization algorithms on weighted networks. While typically implemented as a centralized subroutine, the ability to perform this task in a fully decentralized way is implicit in a number of biological systems. Thus, a natural question is whether this task can provably be accomplished in an efficient way by a network of agents executing a simple protocol.

We provide a positive answer, proposing two distributed approaches to electrical flow computation on a weighted network: a deterministic process mimicking Jacobi's iterative method for solving linear systems, and a randomized token diffusion process, based on revisiting a classical random walk process on a graph with an absorbing node. We show that both processes converge to a solution of Kirchhoff's node potential equations, derive bounds on their convergence rates in terms of the weights of the network, and analyze their time and message complexity.

Contact

Emanuele Natale
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Tags, Category, Keywords and additional notes

Paper accepted to AAMAS18.
ArXiv version: https://arxiv.org/abs/1804.06127

Emanuele Natale, 05/23/2018 15:54
Emanuele Natale, 05/17/2018 00:00 -- Created document.