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What and Who
Title:Pooling or Sampling: Collective Dynamics for Electrical Flow Estimation
Speaker:Emanuele Natale
coming from:Max-Planck-Institut für Informatik - D1
Speakers Bio:
Event Type:AG1 Mittagsseminar (own work)
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Level:AG Audience
Date, Time and Location
Date:Thursday, 24 May 2018
Duration:30 Minutes
Building:E1 4
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.

Name(s):Emanuele Natale
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Note:Paper accepted to AAMAS18.
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Created:Emanuele Natale, 05/17/2018 12:00 AM Last modified:Uwe Brahm/MPII/DE, 05/24/2018 04:01 AM
  • Emanuele Natale, 05/23/2018 03:54 PM
  • Emanuele Natale, 05/17/2018 12:00 AM -- Created document.