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.
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.
Nominated by the University of Washington an outstanding Ph.D. thesis Examines the role of network structure in system dynamics Describes a new method to adaptively improve performance by rewiring and reweighting the network topology
Airlie Chapman
Advection Properties Cartesian Product Digraph Automorphisms Distributed Online Topology Network Identification Network Tomography Network Topology Semi-autonomous Networks Z-Matrix Networks