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Convergence of a Multi-Agent Projected Stochastic Gradient Algorithm for Non-Convex Optimization
We introduce a new framework for the convergence analysis of a class of distributed constrained non-convex optimization algorithms in multi-agent systems. The aim is to search for local minimizers of a non-convex objective function which is supposed to be a sum of local utility functions of the agents. The algorithm …