Realistic, mathematically tractable graph generation and evolution, using kronecker multiplication
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
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We introduce an adaptive graph model where strategy assigned vertices reproduce themselves (having offspring with the same neighbourhood) and unfit vertices get removed. We study how different games cause different graphs to evolve. Under some games graphs grow and break into self replicating structures. Small initial graphs can lead to the generation of vast 'ecosystems' containing thousands of kinds of structures that change and make copies of one another. Understanding how local interactions induce self replication is important to biology. We examine self replicative processes under various games. We investigate how resilient these processes are to stochasticity and we introduce several modified growth models where analysis of the dynamics is easier.