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This thesis analyzes and explores the design of controlled networked dynamic systems - dubbed semi-autonomous networks. The work approaches the problem of effective control of semi-autonomous networks from three fronts: protocols which are run on individual agents in the network; the network interconnection topology design; and efficient modeling of these often large-scale networks. The author extended the popular consensus protocol to advection and nonlinear consensus. The network redesign algorithms are supported by a game-theoretic and an online learning regret analysis.
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