relation: http://eprints.imtlucca.it/2480/
title: Sparse solutions to the average consensus problem via L1-Norm regularization of the fastest mixing Markov-Chain problem
creator: Gnecco, Giorgio
creator: Morisi, Rita
creator: Bemporad, Alberto
subject: QA75 Electronic computers. Computer science
description: In the “consensus problem” on multi-agent systems, in which the states of the agents are “opinions”, the agents aim at reaching a common opinion (or “consensus state”) through local exchange of information. An important design problem is to choose the degree of interconnection of the subsystems so as to achieve a good trade-off between a small number of interconnections and a fast convergence to the consensus state, which is the average of the initial opinions under mild conditions. This paper addresses this problem through l1-norm regularized versions of the well-known fastest mixing Markov-chain problem, which are investigated theoretically. In particular, it is shown that such versions can be interpreted as “robust” forms of the fastest mixing Markov-chain problem. Theoretical results useful to guide the choice of the regularization parameters are also provided, together with a numerical example.
publisher: IEEE
date: 2014-12
type: Book Section
type: PeerReviewed
identifier:   Gnecco, Giorgio and Morisi, Rita and Bemporad, Alberto  Sparse solutions to the average consensus problem via L1-Norm regularization of the fastest mixing Markov-Chain problem.   In:  Proceedings of the 53rd Annual Conference on Decision and Control (CDC).   IEEE, pp. 2228-2233.  ISBN 978-1-4799-7746-8       (2014)  
relation: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7039729&isnumber=7039338
relation: 10.1109/CDC.2014.7039729