Evolutionary dynamics on evolving graphsIkica, Barbara (Avtor) Konvalinka, Matjaž (Mentor) Perc, Matjaž (Komentor) evolutionary game theoryevolutionary dynamicsdynamical processes on graphsmean-field approximationclustering algorithmscomplex networkscontagion processesthreshold modelsevolutionary graph theorymultilayer graphsco-evolving graphsAt the core of any system of interacting entities lie evolution, its driving force of change, and a graph, encoding its structure. In this thesis we investigate how the former affects the latter, and vice versa, whereby we resort to the tools of evolutionary game theory, population dynamics, and graph theory. We begin our journey by considering evolutionary dynamics as they unfold in the absence of population structure from a deterministic and stochastic point of view, then steer to the realm of static graphs endowed with evolutionary games subject to a host of imitation processes, and, at last, stop for a while to leverage the knowledge acquired along the way to develop the modified Petford--Welsh algorithm, a highly scalable decentralised heuristic approach to cluster detection. Picking up where we left off, we then expound on more elaborate forms of imitation dynamics by paying a visit to a plethora of models of contagion, cascade, and consensus dynamics. Soon thereafter, we leave behind the world of simple graphs, enter the domain of multilayer and evolving graphs, and examine how they co-evolve with the evolutionary processes pertaining to them. Finally, we reach our destination, where we put to use the theory that we have become acquainted with to devise a model of the flow of the news across a co-evolving graph comprised of a layer of news providers and a layer of news consumers.20192019-12-20 07:45:04Doktorsko delo/naloga113311UDK: 519.8VisID: 106239COBISS_ID: 18863449sl