Distributed Stochastic Optimization for Constrained and Unconstrained Optimization
Pascal Bianchi, Jérémie Jakubowicz · 2011
In this paper, we analyze the convergence of a distributed Robbins-Monro algorithm for both constrained and unconstrained optimization in multi-agent systems. The algorithm searches local minima of a (nonconvex) objective function which is supposed to coincide with a sum of local utility functions