@inproceedings{a3bfd15e92f24211a0ca03124814e63c,

title = "Distributed multi-agent convex optimization over random digraphs",

abstract = "In this paper, we consider an unconstrained collaborative optimization of a sum of convex functions where agents make decisions using local information in the presence of random communication topologies. We recast the problem as a minimization of the sum of convex functions over a constraint set defined as the set of fixed value points of a random operator derived from weighted matrix of a random graph. This formulation does not need the weighted matrix of the graph to be independent and identically distributed. We define a novel optimization problem which includes the formulated distributed optimization problem as a special case. We propose a discrete algorithm for converging in mean square to the solution of the optimization problem under suitable assumptions. Numerical examples illustrate the convergence of the proposed algorithms.",

author = "Alaviani, {S. Sh} and N. Elia",

year = "2017",

month = jun,

day = "29",

doi = "10.23919/ACC.2017.7963776",

language = "English (US)",

series = "Proceedings of the American Control Conference",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "5288--5293",

booktitle = "2017 American Control Conference, ACC 2017",

note = "2017 American Control Conference, ACC 2017 ; Conference date: 24-05-2017 Through 26-05-2017",

}