Multi-agent Online Optimization

Multi-agent Online Optimization

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This monograph provides an overview of distributed online optimization in multi-agent systems. Online optimization approaches planning and decision problems from a robust learning perspective, where one learns through feedback from sequentially arriving costs, resembling a game between a learner (agent) and the environment. Recently, multi-agent systems have become important in diverse areas including smart power grids, communication networks, machine learning, and robotics, where agents work with decentralized data, costs, and decisions to collectively minimize a system-wide cost. In such set...