Accession Number:

AD1022782

Title:

Distributed Information Fusion through Advanced Multi-Agent Control

Descriptive Note:

Technical Report,14 May 2014,13 May 2016

Corporate Author:

NATIONAL ICT AUSTRALIA LIMITED EVELEIGH Australia

Personal Author(s):

Report Date:

2016-09-09

Pagination or Media Count:

5.0

Abstract:

Distributed consensus in the Wasserstein metric space of probability measures was the primary topic of investigation under this project. Convergence of each agents or nodes measure to a common probability measure is proven under a weak network connectivity condition. The common measure reached at each agent is one minimizing a weighted sum of its Wasserstein distance to all initial agent measures. This measure is known as the Wasserstein barycenter. Special cases involving Gaussian measures, empirical measures, and time-invariant network topologies are considered, where convergence rates and average-consensus results are given. This algorithm has potential applicability in computer vision, machine learning and distributed estimation, etc. A number of other topics in distributed and Monte-Carlo estimation were also considered including distributed information fusion under unknown correlations large-scale sequential Monte-Carlo methods optimal controller approximation via Monte-Carlo methods score and information matrix approximation via sequential Monte-Carlo methods.

Subject Categories:

  • Numerical Mathematics
  • Statistics and Probability
  • Computer Programming and Software
  • Computer Systems

Distribution Statement:

APPROVED FOR PUBLIC RELEASE