Upload
henry-mcgowan
View
24
Download
0
Embed Size (px)
DESCRIPTION
Distributed Agreement Algorithms. Final MURI Review Meeting John N. Tsitsiklis December 2, 2005. The Problem. Each sensor has a number x i They wish to reach agreement on a common value: Some value in the range [Min x i , Max x i ], or The average of their values - PowerPoint PPT Presentation
Citation preview
Distributed Agreement Algorithms
Final MURI Review Meeting
John N. TsitsiklisDecember 2, 2005
The Problem
Each sensor has a number xi
They wish to reach agreement on a common value:
Some value in the range [Min xi , Max xi], or The average of their values
Using a distributed algorithm Without assuming synchronization Without preexisting infrastructure (such as
a spanning tree)
Motivation
Fusion of individual estimates(or of likelihood ratios)
Agreement on a pending decision Load balancing
Multiagent coordination and control Flocking, cooperative control….
The Agreement Algorithm [JNT et al. 1984-89]
Special cases: • Equal weight to yourself and
messages just received
• Pairwise averaging
Assumptions
Convergence Theory
Under Bounded Asynchronism Convergence to a common value Average preserving variants:
convergence to the average of initial values Convergence happens at a geometric rate Even in the presence of communication delays
(update using outdated values of others)
Impact of Initial Values Non-average-preserving cases Equal weights
Starting values in [0,1]
Fixed graph Limit as high as 1(1/n)
Time-Varying graph Limit as high as
Speed of Convergence
Fixed graphs:(tight for “bad graphs”)
Changing graphs:Have variation of the algorithm that guarantees:
References V. D. Blondel, J. M. Hendrickx, A. Olshevsky, and J. N. Tsitsiklis, “Convergence in
Multiagent Coordination, Consensus, and Flocking,” in Proceedings of the Joint 44th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC'05)} Seville, Spain, December 2005.
A. Olshevsky, MS thesis, EECS, MIT, in preparation.
J. N. Tsitsiklis, ``Problems in Decentralized Decision Making and Computation", Ph.D. Thesis, Department of EECS, MIT, November 1984.
D. P. Bertsekas and J. N. Tsitsiklis, Parallel and Distributed Computation: Numerical Methods, Prentice Hall, 1989.
J. N. Tsitsiklis, D. P. Bertsekas and M. Athans, “Distributed Asynchronous Deterministic and Stochastic Gradient Optimization Algorithms", IEEE Transactions on Automatic Control}, Vol. 31, No. 9, 1986, pp. 803-812.