Constrained Consensus and Optimization in Multi-Agent Networks
A. NedićIndustrial and Enterprise Systems Engineering Department, University of Illinois, Urbana-Champaign, Urbana, IL, USAAsuman OzdaglarLaboratory of Information and Decision Systems, Electrical Engineering and Computer Science Department, Massachusetts Institute of Technology, Cambridge, MA, USAPablo A. ParriloLaboratory of Information and Decision Systems, Electrical Engineering and Computer Science Department, Massachusetts Institute of Technology, Cambridge, MA, USA
2010en
ABI
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<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> We present distributed algorithms that can be used by multiple agents to align their estimates with a particular value over a network with time-varying connectivity. Our framework is general in that this value can represent a consensus value among multiple agents or an optimal solution of an optimization problem, where the global objective function is a combination of local agent objective functions. Our main focus is on constrained problems where the estimates of each agent are restricted to lie in different convex sets. </para>
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